title stringlengths 2 287 | abstract stringlengths 0 5.14k ⌀ | journal stringlengths 4 184 | date timestamp[s] | authors listlengths 1 57 | doi stringlengths 16 6.63k ⌀ |
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Biomarkers extracted by fully automated body composition analysis from chest CT correlate with SARS-CoV-2 outcome severity. | The complex process of manual biomarker extraction from body composition analysis (BCA) has far restricted the analysis of SARS-CoV-2 outcomes to small patient cohorts and a limited number of tissue types. We investigate the association of two BCA-based biomarkers with the development of severe SARS-CoV-2 infections fo... | Scientific reports | 2022-10-01T00:00:00 | [
"RenéHosch",
"SimoneKattner",
"Marc MoritzBerger",
"ThorstenBrenner",
"JohannesHaubold",
"JensKleesiek",
"SvenKoitka",
"LennardKroll",
"AnisaKureishi",
"NilsFlaschel",
"FelixNensa"
] | 10.1038/s41598-022-20419-w
10.1016/j.dsx.2020.06.060
10.2196/26075
10.1038/s41586-020-2521-4
10.1016/S2213-8587(21)00089-9
10.1016/j.clnesp.2020.09.018
10.1186/s12911-021-01576-w
10.1016/j.imu.2021.100564
10.1016/j.isci.2021.103523
10.1016/j.metabol.2020.154378
10.1093/bja/aev541
10.1007/s00261-020-02693-2
10.1186/s129... |
AI in Health Science: A Perspective. | By helping practitioners understand complicated and varied types of data, Artificial Intelligence (AI) has influenced medical practice deeply. It is the use of a computer to mimic intelligent behaviour. Many medical professions, particularly those reliant on imaging or surgery, are progressively developing AI. While AI... | Current pharmaceutical biotechnology | 2022-10-01T00:00:00 | [
"RaghavMishra",
"KajalChaudhary",
"IshaMishra"
] | 10.2174/1389201023666220929145220 |
COVID-19 Semantic Pneumonia Segmentation and Classification Using Artificial Intelligence. | Coronavirus 2019 (COVID-19) has become a pandemic. The seriousness of COVID-19 can be realized from the number of victims worldwide and large number of deaths. This paper presents an efficient deep semantic segmentation network (DeepLabv3Plus). Initially, the dynamic adaptive histogram equalization is utilized to enhan... | Contrast media & molecular imaging | 2022-10-01T00:00:00 | [
"Mohammed JAbdulaal",
"Ibrahim MMehedi",
"Abdullah MAbusorrah",
"Abdulah JezaAljohani",
"Ahmad HMilyani",
"Md MasudRana",
"MohamedMahmoud"
] | 10.1155/2022/5297709
10.1109/tnnls.2020.2995800
10.1109/tnnls.2017.2766168
10.1016/j.media.2020.101836
10.1109/access.2020.3016780
10.1016/j.mehy.2020.109761
10.1016/j.imu.2020.100360
10.1016/j.knosys.2020.106270
10.1016/j.asoc.2020.106580
10.1109/ICNN.1993.298572
10.1109/tmi.2016.2528162
10.1007/s13246-020-00888-x
10.... |
A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques. | COVID-19 outbreak has become one of the most challenging problems for human being. It is a communicable disease caused by a new coronavirus strain, which infected over 375 million people already and caused almost 6 million deaths. This paper aims to develop and design a framework for early diagnosis and fast classifica... | Computer methods and programs in biomedicine | 2022-09-30T00:00:00 | [
"SantoshKumar",
"Mithilesh KumarChaube",
"Saeed HamoodAlsamhi",
"Sachin KumarGupta",
"MohsenGuizani",
"RaffaeleGravina",
"GiancarloFortino"
] | 10.1016/j.cmpb.2022.107109
10.1109/TDSC.2022.3144657 |
A Deep Learning based Solution (Covi-DeteCT) Amidst COVID-19. | The whole world has been severely affected due to the COVID-19 pandemic. The rapid and large-scale spread has caused immense pressure on the medical sector hence increasing the chances of false detection due to human errors and mishandling of reports. At the time of outbreaks of COVID-19, there is a crucial shortage of... | Current medical imaging | 2022-09-30T00:00:00 | [
"KavitaPandey"
] | 10.2174/1573405618666220928145344 |
IEViT: An enhanced vision transformer architecture for chest X-ray image classification. | Chest X-ray imaging is a relatively cheap and accessible diagnostic tool that can assist in the diagnosis of various conditions, including pneumonia, tuberculosis, COVID-19, and others. However, the requirement for expert radiologists to view and interpret chest X-ray images can be a bottleneck, especially in remote an... | Computer methods and programs in biomedicine | 2022-09-27T00:00:00 | [
"Gabriel IluebeOkolo",
"StamosKatsigiannis",
"NaeemRamzan"
] | 10.1016/j.cmpb.2022.107141 |
E-GCS: Detection of COVID-19 through classification by attention bottleneck residual network. | Recently, the coronavirus disease 2019 (COVID-19) has caused mortality of many people globally. Thus, there existed a need to detect this disease to prevent its further spread. Hence, the study aims to predict COVID-19 infected patients based on deep learning (DL) and image processing.
The study intends to classify t... | Engineering applications of artificial intelligence | 2022-09-27T00:00:00 | [
"TAhila",
"A CSubhajini"
] | 10.1016/j.engappai.2022.105398 |
Application of Deep Learning Techniques in Diagnosis of Covid-19 (Coronavirus): A Systematic Review. | Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth century. Covid-19 has already endangered the lives of millions of people worldwide due to its acute pulmonary effects. Image-based diagnostic techniques like X-ray, CT, and ultrasound are commonly employed to get a quick and reliab... | Neural processing letters | 2022-09-27T00:00:00 | [
"Yogesh HBhosale",
"K SridharPatnaik"
] | 10.1007/s11063-022-11023-0
10.1101/2020.02.25.20021568
10.1016/j.scs.2020.102571
10.1109/ACCESS.2021.3058066
10.1002/jmv.26709
10.1109/ACCESS.2020.3003810
10.33889/IJMEMS.2020.5.4.052
10.1080/14737159.2021.1962708
10.1016/j.matpr.2020.06.245
10.1016/j.jiph.2020.03.019
10.1080/14737159.2020.1757437
10.1109/ACCESS.2021.3... |
Analysis of the Causes of Solitary Pulmonary Nodule Misdiagnosed as Lung Cancer by Using Artificial Intelligence: A Retrospective Study at a Single Center. | Artificial intelligence (AI) adopting deep learning technology has been widely used in the med-ical imaging domain in recent years. It realized the automatic judgment of benign and malig-nant solitary pulmonary nodules (SPNs) and even replaced the work of doctors to some extent. However, misdiagnoses can occur in certa... | Diagnostics (Basel, Switzerland) | 2022-09-24T00:00:00 | [
"Xiong-YingWu",
"FanDing",
"KunLi",
"Wen-CaiHuang",
"YongZhang",
"JianZhu"
] | 10.3390/diagnostics12092218
10.1016/j.chest.2017.01.018
10.1148/radiol.2017161659
10.1109/TMI.2016.2629462
10.1016/j.media.2017.06.015
10.1002/mp.12846
10.1109/TBME.2016.2613502
10.1038/srep24454
10.1016/j.cell.2020.04.045
10.3390/cancers12082211
10.1056/NEJMoa2001316
10.1155/2017/4067832
10.1038/srep46479
10.1371/jour... |
Segmentation-Based Classification Deep Learning Model Embedded with Explainable AI for COVID-19 Detection in Chest X-ray Scans. | Background and Motivation: COVID-19 has resulted in a massive loss of life during the last two years. The current imaging-based diagnostic methods for COVID-19 detection in multiclass pneumonia-type chest X-rays are not so successful in clinical practice due to high error rates. Our hypothesis states that if we can hav... | Diagnostics (Basel, Switzerland) | 2022-09-24T00:00:00 | [
"NoneNillmani",
"NeerajSharma",
"LucaSaba",
"Narendra NKhanna",
"Mannudeep KKalra",
"Mostafa MFouda",
"Jasjit SSuri"
] | 10.3390/diagnostics12092132
10.1371/journal.pone.0249788
10.1016/j.compbiomed.2020.103960
10.1186/s13244-022-01176-w
10.1007/s10554-020-02089-9
10.1001/jama.2020.3786
10.1016/j.acra.2015.12.010
10.1148/radiol.2015150425
10.1118/1.2836950
10.1016/j.ejrad.2019.02.038
10.1038/s42256-020-0186-1
10.1016/j.zemedi.2018.11.002... |
Identification of micro- and nanoplastics released from medical masks using hyperspectral imaging and deep learning. | Apart from other severe consequences, the COVID-19 pandemic has inflicted a surge in personal protective equipment usage, some of which, such as medical masks, have a short effective protection time. Their misdisposition and subsequent natural degradation make them huge sources of micro- and nanoplastic particles. To b... | The Analyst | 2022-09-21T00:00:00 | [
"IlnurIshmukhametov",
"SvetlanaBatasheva",
"RawilFakhrullin"
] | 10.1039/d2an01139e |
Automated Lung Segmentation from Computed Tomography Images of Normal and COVID-19 Pneumonia Patients. | Automated image segmentation is an essential step in quantitative image analysis. This study assesses the performance of a deep learning-based model for lung segmentation from computed tomography (CT) images of normal and COVID-19 patients.
A descriptive-analytical study was conducted from December 2020 to April 2021 o... | Iranian journal of medical sciences | 2022-09-20T00:00:00 | [
"FaezeGholamiankhah",
"SamanehMostafapour",
"NouraddinAbdi Goushbolagh",
"SeyedjafarShojaerazavi",
"ParvanehLayegh",
"Seyyed MohammadTabatabaei",
"HosseinArabi"
] | 10.30476/IJMS.2022.90791.2178
10.30476/ijms.2020.85869.1549
10.30476/ijms.2020.87233.1730
10.1109/TMI.2020.3001810
10.1109/TBDATA.2021.3056564
10.1109/TMI.2020.2996645
10.1016/j.media.2020.101794
10.1109/ICBME.2010.5704968
10.1016/j.radphyschem.2021.109666
10.1148/radiol.2020200642
10.1101/2020.03.12.20027185
10.1016/j... |
Detection of COVID-19 Infection in CT and X-ray images using transfer learning approach. | The infection caused by the SARS-CoV-2 (COVID-19) pandemic is a threat to human lives. An early and accurate diagnosis is necessary for treatment.
The study presents an efficient classification methodology for precise identification of infection caused by COVID-19 using CT and X-ray images.
The depthwise separable conv... | Technology and health care : official journal of the European Society for Engineering and Medicine | 2022-09-13T00:00:00 | [
"AlokTiwari",
"SumitTripathi",
"Dinesh ChandraPandey",
"NeerajSharma",
"ShiruSharma"
] | 10.3233/THC-220114 |
A Novel Method for COVID-19 Detection Based on DCNNs and Hierarchical Structure. | The worldwide outbreak of the new coronavirus disease (COVID-19) has been declared a pandemic by the World Health Organization (WHO). It has a devastating impact on daily life, public health, and global economy. Due to the highly infectiousness, it is urgent to early screening of suspected cases quickly and accurately.... | Computational and mathematical methods in medicine | 2022-09-13T00:00:00 | [
"YuqinLi",
"KeZhang",
"WeiliShi",
"ZhengangJiang"
] | 10.1155/2022/2484435
10.1016/j.bbe.2020.08.008
10.1016/j.irbm.2020.05.003
10.1007/s10044-021-00984-y
10.7717/peerj-cs.313
10.1080/07391102.2020.1788642
10.1016/j.compbiomed.2020.103792
10.1101/2020.05.12.20099937
10.1117/12.2581496
10.1155/2022/6185013
10.1016/j.mehy.2020.109761
10.1016/j.patrec.2021.11.020
10.1016/B97... |
Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks. | Journal of medical imaging (Bellingham, Wash.) | 2022-09-13T00:00:00 | [
"AdityaKillekar",
"KajetanGrodecki",
"AndrewLin",
"SebastienCadet",
"PriscillaMcElhinney",
"AryabodRazipour",
"CatoChan",
"Barry DPressman",
"PeterJulien",
"PeterChen",
"JuditSimon",
"PalMaurovich-Horvat",
"NicolaGaibazzi",
"UditThakur",
"ElisabettaMancini",
"CeciliaAgalbato",
"JiroM... | 10.1117/1.JMI.9.5.054001
10.1016/j.ajic.2020.07.011
10.1007/s00330-020-07033-y
10.1038/s41598-020-80061-2
10.1148/rg.2020200159
10.1148/radiol.2020200463
10.1148/radiol.2020200843
10.1148/radiol.2020200370
10.1007/s00330-020-06817-6
10.1148/ryct.2020200047
10.1148/ryai.2020200048
10.1148/ryct.2020200441
10.1148/ryct.20... | |
Lung image segmentation based on DRD U-Net and combined WGAN with Deep Neural Network. | COVID-19 is a hot issue right now, and it's causing a huge number of infections in people, posing a grave threat to human life. Deep learning-based image diagnostic technology can effectively enhance the deficiencies of the current main detection method. This paper proposes a multi-classification model diagnosis based ... | Computer methods and programs in biomedicine | 2022-09-12T00:00:00 | [
"LuoyuLian",
"XinLuo",
"CanyuPan",
"JinlongHuang",
"WenshanHong",
"ZhendongXu"
] | 10.1016/j.cmpb.2022.107097 |
Detection of COVID-19 in Point of Care Lung Ultrasound. | The coronavirus disease 2019 (COVID-19) evolved into a global pandemic, responsible for a significant number of infections and deaths. In this scenario, point-of-care ultrasound (POCUS) has emerged as a viable and safe imaging modality. Computer vision (CV) solutions have been proposed to aid clinicians in POCUS image ... | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference | 2022-09-11T00:00:00 | [
"JoanaMaximino",
"MiguelCoimbra",
"JoaoPedrosa"
] | 10.1109/EMBC48229.2022.9871235 |
Dynamic Classification of Imageless Bioelectrical Impedance Tomography Features with Attention-Driven Spatial Transformer Neural Network. | Point-of-Care monitoring devices have proven to be pivotal in the timely screening and intervention of critical care patients. The urgent demands for their deployment in the COVID-19 pandemic era has translated into the escalation of rapid, reliable, and low-cost monitoring systems research and development. Electrical ... | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference | 2022-09-11T00:00:00 | [
"MingdeZheng",
"HassanJahanandish",
"HongweiLi"
] | 10.1109/EMBC48229.2022.9870921 |
Transfer Learning for Automated COVID-19 B-Line Classification in Lung Ultrasound. | Lung ultrasound (LUS) as a diagnostic tool is gaining support for its role in the diagnosis and management of COVID-19 and a number of other lung pathologies. B-lines are a predominant feature in COVID-19, however LUS requires a skilled clinician to interpret findings. To facilitate the interpretation, our main objecti... | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference | 2022-09-11T00:00:00 | [
"Joseph RPare",
"Lars AGjesteby",
"Brian ATelfer",
"Melinda MTonelli",
"Megan MLeo",
"EhabBillatos",
"JonathanScalera",
"Laura JBrattain"
] | 10.1109/EMBC48229.2022.9871894 |
Wasserstein GAN based Chest X-Ray Dataset Augmentation for Deep Learning Models: COVID-19 Detection Use-Case. | The novel coronavirus infection (COVID-19) is still continuing to be a concern for the entire globe. Since early detection of COVID-19 is of particular importance, there have been multiple research efforts to supplement the current standard RT-PCR tests. Several deep learning models, with varying effectiveness, using C... | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference | 2022-09-11T00:00:00 | [
"B ZahidHussain",
"IfrahAndleeb",
"Mohammad SamarAnsari",
"Amit MaheshJoshi",
"NadiaKanwal"
] | 10.1109/EMBC48229.2022.9871519 |
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation. | Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation. However, deep learning models are not trusted in the clinical routine due to failing silently on out-of-distribution (OOD... | Medical image analysis | 2022-09-10T00:00:00 | [
"CamilaGonzález",
"KarolGotkowski",
"MoritzFuchs",
"AndreasBucher",
"ArminDadras",
"RicardaFischbach",
"Isabel JasminKaltenborn",
"AnirbanMukhopadhyay"
] | 10.1016/j.media.2022.102596
10.7937/K9/TCIA.2015.zF0vlOPv
10.5281/zenodo.3757476
10.1016/j.cmpb.2021.106236
10.1055/a-1544-2240 |
COVID-19 diagnosis via chest X-ray image classification based on multiscale class residual attention. | Aiming at detecting COVID-19 effectively, a multiscale class residual attention (MCRA) network is proposed via chest X-ray (CXR) image classification. First, to overcome the data shortage and improve the robustness of our network, a pixel-level image mixing of local regions was introduced to achieve data augmentation a... | Computers in biology and medicine | 2022-09-10T00:00:00 | [
"ShangwangLiu",
"TongboCai",
"XiufangTang",
"YangyangZhang",
"ChanggengWang"
] | 10.1016/j.compbiomed.2022.106065
10.1016/j.compbiomed.2022.105350
10.1109/TIP.2021.3058783
10.1007/s00330-020-07268-9
10.1109/TNNLS.2021.3086570
10.1109/TBDATA.2017.2717439
10.1007/s11063-021-10569-9
10.32604/cmes.2020.09463
10.1016/j.micpro.2020.103282
10.2174/1574893615666200207094357
10.1016/j.compbiomed.2022.105383... |
Semantic-Powered Explainable Model-Free Few-Shot Learning Scheme of Diagnosing COVID-19 on Chest X-Ray. | Chest X-ray (CXR) is commonly performed as an initial investigation in COVID-19, whose fast and accurate diagnosis is critical. Recently, deep learning has a great potential in detecting people who are suspected to be infected with COVID-19. However, deep learning resulting with black-box models, which often breaks dow... | IEEE journal of biomedical and health informatics | 2022-09-09T00:00:00 | [
"YihangWang",
"ChunjuanJiang",
"YouqingWu",
"TianxuLv",
"HengSun",
"YuanLiu",
"LihuaLi",
"XiangPan"
] | 10.1109/JBHI.2022.3205167 |
Ensemble of Deep Neural Networks based on Condorcet's Jury Theorem for screening Covid-19 and Pneumonia from radiograph images. | COVID-19 detection using Artificial Intelligence and Computer-Aided Diagnosis has been the subject of several studies. Deep Neural Networks with hundreds or even millions of parameters (weights) are referred to as "black boxes" because their behavior is difficult to comprehend, even when the model's structure and weigh... | Computers in biology and medicine | 2022-09-06T00:00:00 | [
"GauravSrivastava",
"NiteshPradhan",
"YashwinSaini"
] | 10.1016/j.compbiomed.2022.105979
10.1109/TII.2021.3057683
10.1109/TII.2021.3057524 |
Deep learning framework for prediction of infection severity of COVID-19. | With the onset of the COVID-19 pandemic, quantifying the condition of positively diagnosed patients is of paramount importance. Chest CT scans can be used to measure the severity of a lung infection and the isolate involvement sites in order to increase awareness of a patient's disease progression. In this work, we dev... | Frontiers in medicine | 2022-09-06T00:00:00 | [
"MehdiYousefzadeh",
"MasoudHasanpour",
"MozhdehZolghadri",
"FatemehSalimi",
"AvaYektaeian Vaziri",
"AbolfazlMahmoudi Aqeel Abadi",
"RamezanJafari",
"ParsaEsfahanian",
"Mohammad-RezaNazem-Zadeh"
] | 10.3389/fmed.2022.940960
10.1016/j.idm.2020.02.002
10.1101/2020.02.27.20028027
10.1101/2020.02.07.937862
10.1148/radiol.2020200642
10.1148/radiol.2020200343
10.1371/journal.pone.0250952
10.1038/nature14539
10.1038/s41598-019-51503-3
10.1038/s41591-019-0447-x
10.1038/s41598-019-56589-3
10.1109/TNNLS.2019.2892409
10.1038... |
A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup. | Most of existing deep learning research in medical image analysis is focused on networks with stronger performance. These networks have achieved success, while their architectures are complex and even contain massive parameters ranging from thousands to millions in numbers. The nature of high dimension and nonconvex ma... | Medical physics | 2022-09-05T00:00:00 | [
"YanLiu",
"MaojunZhang",
"ZhiweiZhong",
"XiangrongZeng"
] | 10.1002/mp.15969 |
Deep Convolutional Neural Network Mechanism Assessment of COVID-19 Severity. | As an epidemic, COVID-19's core test instrument still has serious flaws. To improve the present condition, all capabilities and tools available in this field are being used to combat the pandemic. Because of the contagious characteristics of the unique coronavirus (COVID-19) infection, an overwhelming comparison with p... | BioMed research international | 2022-09-03T00:00:00 | [
"JNirmaladevi",
"MVidhyalakshmi",
"E BijolinEdwin",
"NVenkateswaran",
"VinayAvasthi",
"Abdullah AAlarfaj",
"Abdurahman HajinurHirad",
"R KRajendran",
"TegegneAyalewHailu"
] | 10.1155/2022/1289221
10.1109/ISMSIT50672.2020.9255149
10.3390/electronics10141677
10.1101/2020.06.25.20140004
10.1002/pa.2537
10.1016/j.asoc.2020.106912
10.1109/SMART-TECH49988.2020.00041
10.1155/2022/4352730
10.3390/a13100249
10.1016/j.idm.2020.03.002
10.1155/2021/5709257
10.1007/s42600-020-00105-4
10.4066/biomedicalr... |
Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest X-ray data. | With the rise and ever-increasing potential of deep learning techniques in recent years, publicly available medical datasets became a key factor to enable reproducible development of diagnostic algorithms in the medical domain. Medical data contains sensitive patient-related information and is therefore usually anonymi... | Scientific reports | 2022-09-02T00:00:00 | [
"KaiPackhäuser",
"SebastianGündel",
"NicolasMünster",
"ChristopherSyben",
"VincentChristlein",
"AndreasMaier"
] | 10.1038/s41598-022-19045-3
10.1378/chest.10-1302
10.1038/s41598-019-56847-4
10.2214/AJR.12.10375
10.1038/nature14539
10.1016/j.zemedi.2018.12.003
10.1016/j.acra.2019.10.006
10.1016/S0197-2456(00)00097-0
10.1007/s40256-020-00420-2
10.1148/radiol.2020192224
10.1007/s10278-006-1051-4
10.1142/S0218488502001648
10.1016/j.cs... |
Point-of-care SARS-CoV-2 sensing using lens-free imaging and a deep learning-assisted quantitative agglutination assay. | The persistence of the global COVID-19 pandemic caused by the SARS-CoV-2 virus has continued to emphasize the need for point-of-care (POC) diagnostic tests for viral diagnosis. The most widely used tests, lateral flow assays used in rapid antigen tests, and reverse-transcriptase real-time polymerase chain reaction (RT-... | Lab on a chip | 2022-09-02T00:00:00 | [
"Colin JPotter",
"YanmeiHu",
"ZhenXiong",
"JunWang",
"EuanMcLeod"
] | 10.1039/d2lc00289b |
Automated COVID-19 Classification Using Heap-Based Optimization with the Deep Transfer Learning Model. | The outbreak of the COVID-19 pandemic necessitates prompt identification of affected persons to restrict the spread of the COVID-19 epidemic. Radiological imaging such as computed tomography (CT) and chest X-rays (CXR) is considered an effective way to diagnose COVID-19. However, it needs an expert's knowledge and cons... | Computational intelligence and neuroscience | 2022-09-02T00:00:00 | [
"BahjatFakieh",
"MahmoudRagab"
] | 10.1155/2022/7508836
10.3390/jpm12020309
10.3390/s21217286
10.3390/ijerph18063056
10.1016/j.patrec.2021.08.018
10.3390/app11199023
10.1016/j.bbe.2020.08.008
10.1155/2020/8828855
10.1016/j.eswa.2020.114054
10.1007/s11760-020-01820-2
10.1016/j.cmpb.2020.105581
10.1109/SSCI47803.2020.9308571
10.3390/s21041480
10.1109/acce... |
COV-RadNet: A Deep Convolutional Neural Network for Automatic Detection of COVID-19 from Chest X-Rays and CT Scans. | With the increase in severity of COVID-19 pandemic situation, the world is facing a critical fight to cope up with the impacts on human health, education and economy. The ongoing battle with the novel corona virus, is showing much priority to diagnose and provide rapid treatment to the patients. The rapid growth of COV... | Computer methods and programs in biomedicine update | 2022-08-31T00:00:00 | [
"Md KhairulIslam",
"Sultana UmmeHabiba",
"Tahsin AhmedKhan",
"FarzanaTasnim"
] | 10.1016/j.cmpbup.2022.100064 |
Chest X-ray analysis empowered with deep learning: A systematic review. | Chest radiographs are widely used in the medical domain and at present, chest X-radiation particularly plays an important role in the diagnosis of medical conditions such as pneumonia and COVID-19 disease. The recent developments of deep learning techniques led to a promising performance in medical image classification... | Applied soft computing | 2022-08-30T00:00:00 | [
"DulaniMeedeniya",
"HasharaKumarasinghe",
"ShammiKolonne",
"ChamodiFernando",
"Isabel De la TorreDíez",
"GonçaloMarques"
] | 10.1016/j.asoc.2022.109319
10.1038/s41392-020-00243-2
10.1148/ryct.2020200028
10.1016/j.compmedimag.2019.05.005
10.1109/42.974918
10.1109/ACCESS.2021.3065965
10.3390/app10020559
10.1007/s13246-020-00865-4
10.1016/B978-0-12-819061-6.00013-6
10.1007/s11633-020-1231-6
10.3390/jimaging6120131
10.1016/j.media.2021.102125
10... |
SEL-COVIDNET: An intelligent application for the diagnosis of COVID-19 from chest X-rays and CT-scans. | COVID-19 detection from medical imaging is a difficult challenge that has piqued the interest of experts worldwide. Chest X-rays and computed tomography (CT) scanning are the essential imaging modalities for diagnosing COVID-19. All researchers focus their efforts on developing viable methods and rapid treatment proced... | Informatics in medicine unlocked | 2022-08-30T00:00:00 | [
"Ahmad AlSmadi",
"AhedAbugabah",
"Ahmad MohammadAl-Smadi",
"SultanAlmotairi"
] | 10.1016/j.imu.2022.101059
10.1145/3447450.3447458
10.1109/ACCESS.2020.3010287
10.48550/ARXIV.1512.03385
10.48550/ARXIV.1801.04381
10.1109/ICCV.2019.00140
10.1109/CVPRW50498.2020.00183 |
HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution. | the automatic segmentation of lung infections in CT slices provides a rapid and effective strategy for diagnosing, treating, and assessing COVID-19 cases. However, the segmentation of the infected areas presents several difficulties, including high intraclass variability and interclass similarity among infected areas, ... | Computers in biology and medicine | 2022-08-28T00:00:00 | [
"YingChen",
"TaohuiZhou",
"YiChen",
"LongfengFeng",
"ChengZheng",
"LanLiu",
"LipingHu",
"BujianPan"
] | 10.1016/j.compbiomed.2022.105981 |
Novel Coronavirus and Common Pneumonia Detection from CT Scans Using Deep Learning-Based Extracted Features. | COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions to date as the vaccines that have been developed do not prevent the disease but rather reduce the severity of the symptoms. Until a vaccine is developed that can prevent COVID-19 infection, the testing of individuals will be a cont... | Viruses | 2022-08-27T00:00:00 | [
"GhazanfarLatif",
"HamdyMorsy",
"AsmaaHassan",
"JaafarAlghazo"
] | 10.3390/v14081667
10.1007/s10044-021-00984-y
10.1016/j.idm.2020.02.002
10.3201/eid1212.060401
10.1136/bmj.m641
10.1001/jama.2020.2565
10.1016/j.dsx.2020.04.012
10.1109/JBHI.2020.3037127
10.1016/j.media.2020.101797
10.1007/s10489-020-02029-z
10.1016/j.susoc.2021.08.001
10.1109/ACCESS.2020.3016780
10.1016/j.eswa.2020.114... |
Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report. | The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and caro... | Journal of cardiovascular development and disease | 2022-08-26T00:00:00 | [
"Narendra NKhanna",
"MaheshMaindarkar",
"AnudeepPuvvula",
"SudipPaul",
"MrinaliniBhagawati",
"PuneetAhluwalia",
"ZoltanRuzsa",
"AdityaSharma",
"SmikshaMunjral",
"RaghuKolluri",
"Padukone RKrishnan",
"Inder MSingh",
"John RLaird",
"MostafaFatemi",
"AzraAlizad",
"Surinder KDhanjil",
"L... | 10.3390/jcdd9080268
10.1007/s10072-021-05756-4
10.3233/JPD-202038
10.3389/fpsyt.2020.590134
10.1001/jama.2020.1585
10.1016/j.compbiomed.2020.103960
10.1186/s13054-020-03062-7
10.1161/CIRCULATIONAHA.112.093245
10.1161/01.ATV.0000051384.43104.FC
10.1016/S0140-6736(20)30937-5
10.1038/s41577-020-0343-0
10.1016/j.atheroscle... |
Artificial intelligence model on chest imaging to diagnose COVID-19 and other pneumonias: A systematic review and meta-analysis. | When diagnosing Coronavirus disease 2019(COVID-19), radiologists cannot make an accurate judgments because the image characteristics of COVID-19 and other pneumonia are similar. As machine learning advances, artificial intelligence(AI) models show promise in diagnosing COVID-19 and other pneumonias. We performed a syst... | European journal of radiology open | 2022-08-24T00:00:00 | [
"Lu-LuJia",
"Jian-XinZhao",
"Ni-NiPan",
"Liu-YanShi",
"Lian-PingZhao",
"Jin-HuiTian",
"GangHuang"
] | 10.1016/j.ejro.2022.100438 |
A dual-stage deep convolutional neural network for automatic diagnosis of COVID-19 and pneumonia from chest CT images. | In the Coronavirus disease-2019 (COVID-19) pandemic, for fast and accurate diagnosis of a large number of patients, besides traditional methods, automated diagnostic tools are now extremely required. In this paper, a deep convolutional neural network (CNN) based scheme is proposed for automated accurate diagnosis of CO... | Computers in biology and medicine | 2022-08-23T00:00:00 | [
"FarhanSadik",
"Ankan GhoshDastider",
"Mohseu RashidSubah",
"TanvirMahmud",
"Shaikh AnowarulFattah"
] | 10.1016/j.compbiomed.2022.105806
10.1101/2020.02.14.20023028 |
Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation. | Variations in COVID-19 lesions such as glass ground opacities (GGO), consolidations, and crazy paving can compromise the ability of solo-deep learning (SDL) or hybrid-deep learning (HDL) artificial intelligence (AI) models in predicting automated COVID-19 lung segmentation in Computed Tomography (CT) from unseen data l... | Journal of medical systems | 2022-08-22T00:00:00 | [
"Jasjit SSuri",
"SushantAgarwal",
"LucaSaba",
"Gian LucaChabert",
"AlessandroCarriero",
"AlessioPaschè",
"PietroDanna",
"ArminMehmedović",
"GavinoFaa",
"TanayJujaray",
"Inder MSingh",
"Narendra NKhanna",
"John RLaird",
"Petros PSfikakis",
"VikasAgarwal",
"Jagjit STeji",
"RajanikantR ... | 10.1007/s10916-022-01850-y
10.23750/abm.v91i1.9397
10.26355/eurrev_202012_24058
10.1016/j.compbiomed.2020.103960
10.1007/s10554-020-02089-9
10.4239/wjd.v12.i3.215
10.26355/eurrev_202108_26464
10.1016/j.clinimag.2021.05.016
10.23750/abm.v92i5.10418
10.52586/5026
10.1148/radiol.2020200432
10.1016/j.ejrad.2020.109041
10.1... |
Psoas muscle metastatic disease mimicking a psoas abscess on imaging. | Here, we report a case of malignant psoas syndrome presented to us during the second peak of the COVID-19 pandemic. Our patient had a medical history of hypertension, recently diagnosed with left iliac deep vein thrombosis and previous breast and endometrial cancers. She presented with exquisite pain and a fixed flexio... | BMJ case reports | 2022-08-20T00:00:00 | [
"ChristopherGunn",
"MazyarFani"
] | 10.1136/bcr-2022-250654
10.1186/1470-7330-14-21
10.1007/s00330-009-1577-1
10.1007/s12094-011-0625-x
10.3892/mco.2018.1635
10.1016/j.jpainsymman.2003.12.018
10.1089/jpm.2014.0387
10.4103/IJPC.IJPC_205_19
10.1080/15360288.2017.1301617
10.1016/S0304-3959(99)00039-1
10.1111/papr.12643
10.1159/000360581
10.2214/ajr.174.2.17... |
Rapid tissue prototyping with micro-organospheres. | In vitro tissue models hold great promise for modeling diseases and drug responses. Here, we used emulsion microfluidics to form micro-organospheres (MOSs), which are droplet-encapsulated miniature three-dimensional (3D) tissue models that can be established rapidly from patient tissues or cells. MOSs retain key biolog... | Stem cell reports | 2022-08-20T00:00:00 | [
"ZhaohuiWang",
"MatteoBoretto",
"RosemaryMillen",
"NaveenNatesh",
"Elena SReckzeh",
"CarolynHsu",
"MarcosNegrete",
"HaipeiYao",
"WilliamQuayle",
"Brook EHeaton",
"Alfred THarding",
"ShreeBose",
"ElseDriehuis",
"JoepBeumer",
"Grecia ORivera",
"Ravian Lvan Ineveld",
"DonaldGex",
"Jes... | 10.1016/j.stemcr.2022.07.016
10.1016/j.copbio.2015.05.003
10.1038/s41556-020-0472-5
10.1038/s41556-018-0143-y
10.1038/s41556-019-0360-z
10.1016/j.medj.2021.08.005
10.1038/s41551-020-0565-2
10.1038/s41596-019-0232-9
10.1038/nm.3388
10.1016/j.cell.2018.07.009
10.1016/j.stem.2022.04.006
10.1158/2159-8290.CD-18-1522
10.339... |
DAFLNet: Dual Asymmetric Feature Learning Network for COVID-19 Disease Diagnosis in X-Rays. | COVID-19 has become the largest public health event worldwide since its outbreak, and early detection is a prerequisite for effective treatment. Chest X-ray images have become an important basis for screening and monitoring the disease, and deep learning has shown great potential for this task. Many studies have propos... | Computational and mathematical methods in medicine | 2022-08-20T00:00:00 | [
"JingyaoLiu",
"JiashiZhao",
"LiyuanZhang",
"YuMiao",
"WeiHe",
"WeiliShi",
"YanfangLi",
"BaiJi",
"KeZhang",
"ZhengangJiang"
] | 10.1155/2022/3836498
10.1016/j.cmpb.2020.105532
10.1148/radiol.2020200642
10.1016/j.inffus.2020.10.004
10.22266/ijies2016.1231.24
10.3390/diagnostics10060358
10.1016/j.chaos.2020.110190
10.1016/j.crad.2020.03.004
10.1016/j.imu.2020.100360
10.1016/j.compeleceng.2020.106765
10.1007/s12559-020-09776-8
10.1016/j.ins.2020.0... |
MFL-Net: An Efficient Lightweight Multi-Scale Feature Learning CNN for COVID-19 Diagnosis From CT Images. | Timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) is crucial in curbing its spread. Slow testing results of reverse transcription-polymerase chain reaction (RT-PCR) and a shortage of test kits have led to consider chest computed tomography (CT) as an alternative screening and diagnostic tool. Many de... | IEEE journal of biomedical and health informatics | 2022-08-19T00:00:00 | [
"Amogh ManojJoshi",
"Deepak RanjanNayak"
] | 10.1109/JBHI.2022.3196489 |
Semi-supervised COVID-19 CT image segmentation using deep generative models. | A recurring problem in image segmentation is a lack of labelled data. This problem is especially acute in the segmentation of lung computed tomography (CT) of patients with Coronavirus Disease 2019 (COVID-19). The reason for this is simple: the disease has not been prevalent long enough to generate a great number of la... | BMC bioinformatics | 2022-08-17T00:00:00 | [
"JudahZammit",
"Daryl L XFung",
"QianLiu",
"Carson Kai-SangLeung",
"PingzhaoHu"
] | 10.1186/s12859-022-04878-6
10.1016/j.cell.2020.04.045
10.1109/TPAMI.2016.2644615
10.1109/TPAMI.2019.2960224
10.1016/j.patcog.2020.107269
10.1186/s12967-021-02992-2 |
CovMnet-Deep Learning Model for classifying Coronavirus (COVID-19). | Diagnosing COVID-19, current pandemic disease using Chest X-ray images is widely used to evaluate the lung disorders. As the spread of the disease is enormous many medical camps are being conducted to screen the patients and Chest X-ray is a simple imaging modality to detect presence of lung disorders. Manual lung diso... | Health and technology | 2022-08-16T00:00:00 | [
"MalathyJawahar",
"Jani AnbarasiL",
"VinayakumarRavi",
"JPrassanna",
"S GracelineJasmine",
"RManikandan",
"RamesSekaran",
"SuthendranKannan"
] | 10.1007/s12553-022-00688-1
10.1016/j.chemolab.2020.104054
10.1007/s10044-021-00984-y
10.1007/s13246-020-00865-4
10.1016/j.ins.2020.09.041
10.1016/j.chaos.2020.109949
10.1016/j.chaos.2020.110242
10.4018/IJSSCI.2020070102
10.4249/scholarpedia.1717
10.1113/jphysiol.1970.sp009022
10.1007/BF00344251
10.1007/s00521-018-3761-... |
Multiclass Classification for Detection of COVID-19 Infection in Chest X-Rays Using CNN. | Coronavirus took the world by surprise and caused a lot of trouble in all the important fields in life. The complexity of dealing with coronavirus lies in the fact that it is highly infectious and is a novel virus which is hard to detect with exact precision. The typical detection method for COVID-19 infection is the R... | Computational intelligence and neuroscience | 2022-08-16T00:00:00 | [
"Rawan SaqerAlharbi",
"Hadeel AysanAlsaadi",
"SManimurugan",
"TAnitha",
"MiniluDejene"
] | 10.1155/2022/3289809
10.1016/j.chaos.2020.110495
10.1016/j.bspc.2022.103561
10.1007/s13755-020-00135-3
10.3390/ijerph18063056
10.1007/978-3-642-15825-4_10
10.3390/s2203121
10.1007/s10489-020-01978-9
10.1016/j.neucom.2021.03.034
10.1016/j.bspc.2021.102920 |
Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry. | In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of 'non visual' markers that con... | Respirology (Carlton, Vic.) | 2022-08-16T00:00:00 | [
"RozemarijnVliegenthart",
"AndreasFouras",
"ColinJacobs",
"NickolasPapanikolaou"
] | 10.1111/resp.14344
10.1097/RLI.0000000000000822
10.1148/radiol.210551
10.1007/s00247-021-05146-0
10.1109/CVPR.2017.369 |
Reinforcement Learning Based Diagnosis and Prediction for COVID-19 by Optimizing a Mixed Cost Function From CT Images. | A novel coronavirus disease (COVID-19) is a pandemic disease has caused 4 million deaths and more than 200 million infections worldwide (as of August 4, 2021). Rapid and accurate diagnosis of COVID-19 infection is critical to controlling the spread of the epidemic. In order to quickly and efficiently detect COVID-19 an... | IEEE journal of biomedical and health informatics | 2022-08-12T00:00:00 | [
"SiyingChen",
"MinghuiLiu",
"PanDeng",
"JialiDeng",
"YiYuan",
"XuanCheng",
"TianshuXie",
"LiboXie",
"WeiZhang",
"HaigangGong",
"XiaominWang",
"LifengXu",
"HongPu",
"MingLiu"
] | 10.1109/JBHI.2022.3197666 |
Detection of COVID-19 from chest X-ray images: Boosting the performance with convolutional neural network and transfer learning. | Coronavirus disease (COVID-19) is a pandemic that has caused thousands of casualties and impacts all over the world. Most countries are facing a shortage of COVID-19 test kits in hospitals due to the daily increase in the number of cases. Early detection of COVID-19 can protect people from severe infection. Unfortunate... | Expert systems | 2022-08-11T00:00:00 | [
"SohaibAsif",
"YiWenhui",
"KamranAmjad",
"HouJin",
"YiTao",
"SiJinhai"
] | 10.1111/exsy.13099
10.1080/07391102.2020.1767212
10.20944/preprints202003.0300.v1 |
A modified DeepLabV3+ based semantic segmentation of chest computed tomography images for COVID-19 lung infections. | Coronavirus disease (COVID-19) affects the lives of billions of people worldwide and has destructive impacts on daily life routines, the global economy, and public health. Early diagnosis and quantification of COVID-19 infection have a vital role in improving treatment outcomes and interrupting transmission. For this p... | International journal of imaging systems and technology | 2022-08-10T00:00:00 | [
"HasanPolat"
] | 10.1002/ima.22772
10.1002/ima.22566
10.1002/ima.22525
10.1016/j.measurement.2020.108288
10.1016/j.mehy.2020.109761
10.1148/radiol.2020200642
10.1016/j.aej.2020.10.046
10.1016/j.media.2017.07.005
10.1016/j.tmaid.2020.101623
10.1016/j.jrid.2020.04.001
10.1111/exsy.12742
10.1049/iet-cvi.2018.5129
10.1049/iet-its.2018.5144... |
Deep Learning-Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs. | Accurate estimation of mortality and time to death at admission for COVID-19 patients is important and several deep learning models have been created for this task. However, there are currently no prognostic models which use end-to-end deep learning to predict time to event for admitted COVID-19 patients using chest ra... | Journal of digital imaging | 2022-08-09T00:00:00 | [
"ToshimasaMatsumoto",
"Shannon LeighWalston",
"MichaelWalston",
"DaijiroKabata",
"YukioMiki",
"MasatsuguShiba",
"DaijuUeda"
] | 10.1007/s10278-022-00691-y
10.7861/clinmed.2020-0214
10.1186/s13613-020-00650-2
10.1093/cid/ciaa414
10.1016/S2213-8587(21)00089-9
10.1001/jama.2018.11100
10.1038/nature14539
10.1186/s12874-018-0482-1
10.1016/j.amjmed.2004.03.020
10.1007/s11547-020-01232-9
10.1007/s10140-020-01808-y
10.1148/radiol.2020201754
10.1148/rad... |
Deep Learning-Aided Automated Pneumonia Detection and Classification Using CXR Scans. | The COVID-19 pandemic has caused a worldwide catastrophe and widespread devastation that reeled almost all countries. The pandemic has mounted pressure on the existing healthcare system and caused panic and desperation. The gold testing standard for COVID-19 detection, reverse transcription-polymerase chain reaction (R... | Computational intelligence and neuroscience | 2022-08-09T00:00:00 | [
"Deepak KumarJain",
"TarishiSingh",
"PraneetSaurabh",
"DhananjayBisen",
"NeerajSahu",
"JayantMishra",
"HabiburRahman"
] | 10.1155/2022/7474304
10.1109/ICDABI51230.2020.9325626
10.1001/jama.2020.1585
10.1016/s0140-6736(20)30211-710.1016/s0140-6736(20)30211-7
10.1056/NEJMoa2001316
10.1016/S0140-6736(20)30183-5
10.1093/clinchem/hvaa029
10.1148/radiol.2020200230
10.2214/AJR.20.23034
10.1007/s10489-020-01826-w
10.1109/ISMSIT.2019.8932878
10.11... |
A Novel Multi-Stage Residual Feature Fusion Network for Detection of COVID-19 in Chest X-Ray Images. | To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due to the limited data, existing models suffer from incapable feature ex... | IEEE transactions on molecular, biological, and multi-scale communications | 2022-08-09T00:00:00 | [
"ZhenyuFang",
"JinchangRen",
"CalumMacLellan",
"HuihuiLi",
"HuiminZhao",
"AmirHussain",
"GiancarloFortino"
] | 10.1109/TMBMC.2021.3099367 |
Deep Learning Based COVID-19 Detection Using Medical Images: Is Insufficient Data Handled Well? | Deep learning is a prominent method for automatic detection of COVID-19 disease using a medical dataset. This paper aims to give a perspective on the data insufficiency issue that exists in COVID-19 detection associated with deep learning. The extensive study of the available datasets comprising CT and X-ray images is ... | Current medical imaging | 2022-08-06T00:00:00 | [
"CarenBabu",
"RahulManohar O",
"D AbrahamChandy"
] | 10.2174/1573405618666220803123626 |
Deep Learning-Based Networks for Detecting Anomalies in Chest X-Rays. | X-ray images aid medical professionals in the diagnosis and detection of pathologies. They are critical, for example, in the diagnosis of pneumonia, the detection of masses, and, more recently, the detection of COVID-19-related conditions. The chest X-ray is one of the first imaging tests performed when pathology is su... | BioMed research international | 2022-08-03T00:00:00 | [
"MalekBadr",
"ShahaAl-Otaibi",
"NazikAlturki",
"TanvirAbir"
] | 10.1155/2022/7833516
10.1201/b10866-37
10.1109/CVPR.2017.369
10.1109/ICSCCC.2018.8703316
10.1016/B978-0-12-816718-2.00008-7
10.1155/2022/1959371
10.1007/978-981-15-4112-4_7
10.3390/jcm11072054
10.23919/MIPRO48935.2020.9245376
10.1155/2022/4569879
10.14569/IJACSA.2021.0121026
10.1109/ELNANO.2018.8477564
10.1155/2021/814... |
Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images. | Corona Virus Disease 2019 (COVID-19) first appeared in December 2019, and spread rapidly around the world. COVID-19 is a pneumonia caused by novel coronavirus infection in 2019. COVID-19 is highly infectious and transmissible. By 7 May 2021, the total number of cumulative number of deaths is 3,259,033. In order to diag... | BMC medical imaging | 2022-07-31T00:00:00 | [
"WeiWang",
"YongbinJiang",
"XinWang",
"PengZhang",
"JiLi"
] | 10.1186/s12880-022-00861-y
10.1016/j.physio.2020.03.003
10.1109/5.726791
10.1109/TIP.2017.2710620
10.2991/ijcis.d.191209.001
10.1186/s12880-019-0399-0
10.1109/TUFFC.2020.3005512
10.1109/ACCESS.2020.3001973
10.7150/ijms.46684
10.1109/TMI.2020.2995508
10.1007/s42979-020-00401-x
10.1007/s42979-020-00335-4
10.1007/s42979-0... |
A comparison of Covid-19 early detection between convolutional neural networks and radiologists. | The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful i... | Insights into imaging | 2022-07-29T00:00:00 | [
"AlbertoAlbiol",
"FranciscoAlbiol",
"RobertoParedes",
"Juana MaríaPlasencia-Martínez",
"AnaBlanco Barrio",
"José M GarcíaSantos",
"SalvadorTortajada",
"Victoria MGonzález Montaño",
"Clara ERodríguez Godoy",
"SarayFernández Gómez",
"ElenaOliver-Garcia",
"Maríade la Iglesia Vayá",
"Francisca L... | 10.1186/s13244-022-01250-3
10.1001/JAMA.2020.21694
10.1007/S00330-020-07347-X
10.1007/S00330-020-06967-7
10.1148/RADIOL.2020201160/ASSET/IMAGES/LARGE/RADIOL.2020201160.FIG6.JPEG
10.1148/RADIOL.2020202944/ASSET/IMAGES/LARGE/RADIOL.2020202944.TBL4.JPEG
10.1148/RADIOL.2020203511/ASSET/IMAGES/LARGE/RADIOL.2020203511.FIG6C.... |
Automatic scoring of COVID-19 severity in X-ray imaging based on a novel deep learning workflow. | In this study, we propose a two-stage workflow used for the segmentation and scoring of lung diseases. The workflow inherits quantification, qualification, and visual assessment of lung diseases on X-ray images estimated by radiologists and clinicians. It requires the fulfillment of two core stages devoted to lung and ... | Scientific reports | 2022-07-28T00:00:00 | [
"Viacheslav VDanilov",
"DianaLitmanovich",
"AlexProutski",
"AlexanderKirpich",
"DatoNefaridze",
"AlexKarpovsky",
"YuriyGankin"
] | 10.1038/s41598-022-15013-z
10.2139/ssrn.3685938
10.1093/cid/ciaa1012
10.1016/j.jaci.2020.04.006
10.1016/j.cmi.2020.04.012
10.1148/ryct.2020200034
10.1148/radiol.2020200527
10.1016/j.chest.2020.04.003
10.1007/s11547-020-01202-1
10.1007/s10489-020-01829-7
10.1016/j.imu.2021.100835
10.1016/j.compbiomed.2020.103869
10.1007... |
Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features. | The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality among COVID-19 patients using clinical and chest radiographic data. Modeling was per... | Tomography (Ann Arbor, Mich.) | 2022-07-28T00:00:00 | [
"Xuan VNguyen",
"EnginDikici",
"SemaCandemir",
"Robyn LBall",
"Luciano MPrevedello"
] | 10.3390/tomography8040151
10.1038/s41586-020-2008-3
10.1148/radiol.2020200490
10.1002/path.5549
10.1148/radiol.2020200642
10.1109/RBME.2020.2987975
10.1016/j.bbe.2020.08.008
10.1038/s41598-020-76550-z
10.1038/s41591-020-0931-3
10.1109/TMI.2020.2993291
10.1148/radiol.2020204226
10.1186/s40537-016-0043-6
10.1007/s10278-0... |
Federated Learning Approach with Pre-Trained Deep Learning Models for COVID-19 Detection from Unsegmented CT images. | (1) Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2. Reverse transcription polymerase chain reaction (RT-PCR) remains the current gold standard for detecting SARS-CoV-2 infections in nasopharyngeal swabs. In Romania, the first reported patient to have contracted COVID-19 wa... | Life (Basel, Switzerland) | 2022-07-28T00:00:00 | [
"Lucian MihaiFlorescu",
"Costin TeodorStreba",
"Mircea-SebastianŞerbănescu",
"MădălinMămuleanu",
"Dan NicolaeFlorescu",
"Rossy VlăduţTeică",
"Raluca ElenaNica",
"Ioana AndreeaGheonea"
] | 10.3390/life12070958
10.3389/fmicb.2020.631736
10.1002/jmv.25766
10.1056/NEJMoa2001017
10.3390/life12010077
10.1148/ryct.2020200034
10.1016/j.jmoldx.2021.04.009
10.47162/RJME.61.2.21
10.1007/s00330-021-07937-3
10.1111/exsy.12759
10.1038/nature14539
10.1016/j.patcog.2021.108081
10.1016/j.asoc.2020.106912
10.1007/s13246-... |
Bag of Tricks for Improving Deep Learning Performance on Multimodal Image Classification. | A comprehensive medical image-based diagnosis is usually performed across various image modalities before passing a final decision; hence, designing a deep learning model that can use any medical image modality to diagnose a particular disease is of great interest. The available methods are multi-staged, with many comp... | Bioengineering (Basel, Switzerland) | 2022-07-26T00:00:00 | [
"Steve AAdeshina",
"Adeyinka PAdedigba"
] | 10.3390/bioengineering9070312
10.1111/exd.13777
10.1109/ACCESS.2020.3016780
10.3390/diagnostics10080565
10.1007/s40747-021-00321-0
10.31083/j.fbl2707198
10.1101/2020.04.24.20078584
10.1109/ACCESS.2020.3010287
10.48550/arXiv.1907.08610
10.1016/j.ibmed.2021.100034
10.3390/bioengineering9040161 |
A Novel Deep Learning and Ensemble Learning Mechanism for Delta-Type COVID-19 Detection. | Recently, the novel coronavirus disease 2019 (COVID-19) has posed many challenges to the research community by presenting grievous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that results in a huge number of mortalities and high morbidities worldwide. Furthermore, the symptoms-based variations in virus... | Frontiers in public health | 2022-07-26T00:00:00 | [
"Habib UllahKhan",
"SulaimanKhan",
"ShahNazir"
] | 10.3389/fpubh.2022.875971
10.1016/j.compbiomed.2020.103805
10.1016/j.eswa.2020.114054
10.1109/INMIC50486.2020.9318212
10.1007/s10489-020-01902-1
10.1109/MITP.2020.3036820
10.1016/j.eswa.2020.113909
10.1056/NEJMoa2001191
10.1016/j.ijid.2020.01.009
10.1056/NEJMc2001468
10.1016/j.compeleceng.2020.106906
10.32604/cmc.2021.... |
A Deep Learning and Handcrafted Based Computationally Intelligent Technique for Effective COVID-19 Detection from X-ray/CT-scan Imaging. | The world has witnessed dramatic changes because of the advent of COVID19 in the last few days of 2019. During the last more than two years, COVID-19 has badly affected the world in diverse ways. It has not only affected human health and mortality rate but also the economic condition on a global scale. There is an urge... | Journal of grid computing | 2022-07-26T00:00:00 | [
"MohammedHabib",
"MuhammadRamzan",
"Sajid AliKhan"
] | 10.1007/s10723-022-09615-0
10.1109/ACCESS.2020.2999468
10.1007/s11063-018-09976-2
10.1109/ACCESS.2017.2789324
10.1007/s10723-020-09506-2
10.1007/s10723-021-09594-8
10.1007/s10723-021-09564-0
10.1016/j.compbiomed.2018.03.016
10.1007/s10723-020-09513-3
10.1007/s10723-021-09590-y
10.1016/j.diii.2020.03.014
10.1016/j.chaos... |
An efficient deep learning-based framework for tuberculosis detection using chest X-ray images. | Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease, decrease mortality risk, and stop transmission to other people. The chest X-ray (CXR) is the top choice for lung disease screening in clinics because it is cost-effective and easily accessible in most countries. However, manua... | Tuberculosis (Edinburgh, Scotland) | 2022-07-26T00:00:00 | [
"AhmedIqbal",
"MuhammadUsman",
"ZohairAhmed"
] | 10.1016/j.tube.2022.102234 |
Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19. | To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations. A published convolutional Siamese neural network-based model previously trained on hospitalized patients with COVID-19 was tuned using 250... | Medicine | 2022-07-23T00:00:00 | [
"Matthew DLi",
"Nishanth TArun",
"MehakAggarwal",
"SharutGupta",
"PraveerSingh",
"Brent PLittle",
"Dexter PMendoza",
"Gustavo C ACorradi",
"Marcelo STakahashi",
"Suely FFerraciolli",
"Marc DSucci",
"MinLang",
"Bernardo CBizzo",
"IttaiDayan",
"Felipe CKitamura",
"JayashreeKalpathy-Crame... | 10.1097/MD.0000000000029587 |
Ftl-CoV19: A Transfer Learning Approach to Detect COVID-19. | COVID-19 is an infectious and contagious disease caused by the new coronavirus. The total number of cases is over 19 million and continues to grow. A common symptom noticed among COVID-19 patients is lung infection that results in breathlessness, and the lack of essential resources such as testing, oxygen, and ventilat... | Computational intelligence and neuroscience | 2022-07-23T00:00:00 | [
"TarishiSingh",
"PraneetSaurabh",
"DhananjayBisen",
"LalitKane",
"MayankPathak",
"G RSinha"
] | 10.1155/2022/1953992
10.15557/pimr.2020.0024
10.1016/j.genrep.2020.100756
10.1109/TAI.2021.3062771
10.1109/tmi.2020.2995508
10.1109/ACCESS.2020.2997311
10.1109/RBME.2020.2987975
10.1109/CANDO-EPE51100.2020.9337794
10.1109/TCYB.2019.2950779
10.1016/j.numecd.2020.07.031
10.1155/2020/9756518
10.1101/2020.10.13.20212035
10... |
Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning. | Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interpretable deep learning algorithm for the diagnosis and prognosis of COVID-19 pneumo... | BMC infectious diseases | 2022-07-22T00:00:00 | [
"Jordan HChamberlin",
"GilbertoAquino",
"SophiaNance",
"AndrewWortham",
"NathanLeaphart",
"NamrataPaladugu",
"SeanBrady",
"HenryBaird",
"MatthewFiegel",
"LoganFitzpatrick",
"MadisonKocher",
"FlorinGhesu",
"AwaisMansoor",
"PhilippHoelzer",
"MathisZimmermann",
"W EnnisJames",
"D Jameso... | 10.1186/s12879-022-07617-7
10.1136/bmj.m2426
10.1007/s11547-020-01232-9
10.1016/j.ijid.2020.05.021
10.1186/s41747-020-00195-w
10.1148/radiol.2021219021
10.1148/ryct.2020200028
10.1186/s43055-020-00296-x
10.1148/ryct.2020200337
10.1148/radiol.2021219022
10.1136/bmj.m1328
10.1016/j.jiph.2020.06.028
10.1109/RBME.2020.2987... |
Simplified Transfer Learning for Chest Radiography Models Using Less Data. | Background Developing deep learning models for radiology requires large data sets and substantial computational resources. Data set size limitations can be further exacerbated by distribution shifts, such as rapid changes in patient populations and standard of care during the COVID-19 pandemic. A common partial mitigat... | Radiology | 2022-07-20T00:00:00 | [
"Andrew BSellergren",
"ChristinaChen",
"ZaidNabulsi",
"YuanzhenLi",
"AaronMaschinot",
"AaronSarna",
"JennyHuang",
"CharlesLau",
"Sreenivasa RajuKalidindi",
"MozziyarEtemadi",
"FlorenciaGarcia-Vicente",
"DavidMelnick",
"YunLiu",
"KrishEswaran",
"DanielTse",
"NeeralBeladia",
"DilipKris... | 10.1148/radiol.212482 |
COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence. | COVID-19 detection and classification using chest X-ray images is a current hot research topic based on the important application known as medical image analysis. To halt the spread of COVID-19, it is critical to identify the infection as soon as possible. Due to time constraints and the expertise of radiologists, manu... | Computational intelligence and neuroscience | 2022-07-19T00:00:00 | [
"Muhammad AttiqueKhan",
"MariumAzhar",
"KainatIbrar",
"AbdullahAlqahtani",
"ShtwaiAlsubai",
"AdelBinbusayyis",
"Ye JinKim",
"ByoungcholChang"
] | 10.1155/2022/4254631
10.3390/diagnostics12030741
10.1038/s41598-022-10723-w
10.1371/journal.pone.0246772
10.1016/j.genhosppsych.2020.07.006
10.1016/j.eng.2020.04.010
10.1002/1096-9071(200103)63:3<259::aid-jmv1010>3.0.co;2-x
10.1016/j.eswa.2020.114054
10.7326/m20-1382
10.1007/s00330-021-07715-1
10.1109/tmi.2016.2553401
... |
A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes. | There is still an urgent need to develop effective treatments to help minimize the cases of severe COVID-19. A number of tools have now been developed and applied to address these issues, such as the use of non-contrast chest computed tomography (CT) for evaluation and grading of the associated lung damage. Here we use... | Methods in molecular biology (Clifton, N.J.) | 2022-07-16T00:00:00 | [
"AmirhosseinSahebkar",
"MitraAbbasifard",
"SamiraChaibakhsh",
"Paul CGuest",
"Mohamad AminPourhoseingholi",
"AmirVahedian-Azimi",
"PrashantKesharwani",
"TannazJamialahmadi"
] | 10.1007/978-1-0716-2395-4_30
10.1039/D0LC01156H
10.1016/j.cie.2021.107235
10.1016/S0140-6736(20)30360-3
10.7150/ijms.50568
10.1186/s12879-021-06528-3
10.1148/radiol.2020200330
10.1148/radiol.2020200343
10.1007/978-3-030-59261-5_24
10.2214/AJR.20.22975
10.1148/radiol.2020200230
10.1021/acsnano.0c02624
10.5114/pjr.2020.9... |
Feature-level ensemble approach for COVID-19 detection using chest X-ray images. | Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), also known as the coronavirus disease 2019 (COVID-19), has threatened many human beings around the world and capsized economies at unprecedented magnitudes. Therefore, the detection of this disease using chest X-ray modalities has played a pivotal role in pr... | PloS one | 2022-07-15T00:00:00 | [
"Thi Kieu KhanhHo",
"JeonghwanGwak"
] | 10.1371/journal.pone.0268430
10.1056/NEJMoa2002032
10.1128/JCM.00512-20
10.1093/cid/ciaa310
10.1002/jmv.26699
10.1038/nature21056
10.1002/jmri.26534
10.1016/j.bspc.2019.101678
10.1016/j.compmedimag.2019.101673
10.1016/j.eswa.2018.04.021
10.1109/ACCESS.2019.2900127
10.1148/radiol.2019182716
10.1016/j.media.2018.03.006
1... |
Classification of COVID-19 from tuberculosis and pneumonia using deep learning techniques. | Deep learning provides the healthcare industry with the ability to analyse data at exceptional speeds without compromising on accuracy. These techniques are applicable to healthcare domain for accurate and timely prediction. Convolutional neural network is a class of deep learning methods which has become dominant in v... | Medical & biological engineering & computing | 2022-07-15T00:00:00 | [
"LokeswariVenkataramana",
"D Venkata VaraPrasad",
"SSaraswathi",
"C MMithumary",
"RKarthikeyan",
"NMonika"
] | 10.1007/s11517-022-02632-x
10.1080/01431169508954507
10.1007/s42979-021-00695-5
10.3390/app10093233
10.1016/j.cell.2018.02.010
10.3390/app8101715
10.1111/j.1440-1843.2006.00947.x
10.1007/s40747-020-00199-4
10.1016/j.bbe.2020.08.008
10.1613/jair.953
10.1504/IJKESDP.2011.039875
10.1613/jair.1.11192
10.1016/j.eswa.2021.11... |
RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights. | Myocarditis is heart muscle inflammation that is becoming more prevalent these days, especially with the prevalence of COVID-19. Noninvasive imaging cardiac magnetic resonance (CMR) can be used to diagnose myocarditis, but the interpretation is time-consuming and requires expert physicians. Computer-aided diagnostic sy... | Contrast media & molecular imaging | 2022-07-15T00:00:00 | [
"Seyed VahidMoravvej",
"RoohallahAlizadehsani",
"SadiaKhanam",
"ZahraSobhaninia",
"AfshinShoeibi",
"FahimeKhozeimeh",
"Zahra AlizadehSani",
"Ru-SanTan",
"AbbasKhosravi",
"SaeidNahavandi",
"Nahrizul AdibKadri",
"Muhammad MokhzainiAzizan",
"NArunkumar",
"U RajendraAcharya"
] | 10.1155/2022/8733632
10.1056/nejmra0800028
10.1016/j.humpath.2005.07.009
10.1007/978-3-030-92238-2_57
10.1007/s00500-014-1334-5
10.1007/s10479-011-0894-3
10.1016/j.knosys.2017.11.029
10.1007/11538059_91
10.1145/1007730.1007735
10.1007/s10489-020-01637-z
10.1109/tkde.2005.95
10.1016/j.knosys.2015.10.012
10.1109/3477.764... |
Non-iterative learning machine for identifying CoViD19 using chest X-ray images. | CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around the world. The last significant variant of this virus, called as omicron, contributed to majority of cases in the third wave across globe. Though lesser in severity as compared to its predecessor, the delta variant, this... | Scientific reports | 2022-07-14T00:00:00 | [
"SahilDalal",
"Virendra PVishwakarma",
"VarshaSisaudia",
"ParulNarwal"
] | 10.1038/s41598-022-15268-6
10.3346/jkms.2020.35.e150
10.1001/jama.2021.2927
10.1016/j.clinimag.2020.04.010
10.1016/j.jcv.2020.104359
10.1016/j.jcv.2020.104356
10.5582/bst.2020.01047
10.1016/j.ajem.2020.09.032
10.1007/s11046-021-00528-2
10.1007/s13246-020-00865-4
10.1109/JBHI.2020.3037127
10.1007/s10096-020-03901-z
10.1... |
Detection of COVID-19 using deep learning techniques and classification methods. | Since the patient is not quarantined during the conclusion of the Polymerase Chain Reaction (PCR) test used in the diagnosis of COVID-19, the disease continues to spread. In this study, it was aimed to reduce the duration and amount of transmission of the disease by shortening the diagnosis time of COVID-19 patients wi... | Information processing & management | 2022-07-14T00:00:00 | [
"ÇinareOğuz",
"MeteYağanoğlu"
] | 10.1016/j.ipm.2022.103025
10.1101/2020.03.12.20027185 |
Computational Intelligence-Based Method for Automated Identification of COVID-19 and Pneumonia by Utilizing CXR Scans. | Chest X-ray (CXR) scans are emerging as an important diagnostic tool for the early spotting of COVID and other significant lung diseases. The recognition of visual symptoms is difficult and can take longer time by radiologists as CXR provides various signs of viral infection. Therefore, artificial intelligence-based me... | Computational intelligence and neuroscience | 2022-07-09T00:00:00 | [
"BhavanaKaushik",
"DeepikaKoundal",
"NeelamGoel",
"AtefZaguia",
"AssayeBelay",
"HamzaTurabieh"
] | 10.1155/2022/7124199
10.1016/j.ijid.2020.01.009
10.4018/ijehmc.20220701.oa4
10.1111/exsy.12749
10.1109/jiot.2018.2802898
10.1109/tkde.2009.191
10.1186/s40537-016-0043-6
10.1109/access.2018.2845399
10.1016/j.eng.2020.04.010
10.1080/07391102.2020.1767212
10.1016/j.compbiomed.2020.103792
10.1109/access.2020.2994762
10.101... |
PCA-Based Incremental Extreme Learning Machine (PCA-IELM) for COVID-19 Patient Diagnosis Using Chest X-Ray Images. | Novel coronavirus 2019 has created a pandemic and was first reported in December 2019. It has had very adverse consequences on people's daily life, healthcare, and the world's economy as well. According to the World Health Organization's most recent statistics, COVID-19 has become a worldwide pandemic, and the number o... | Computational intelligence and neuroscience | 2022-07-09T00:00:00 | [
"VinodKumar",
"SougatamoyBiswas",
"Dharmendra SinghRajput",
"HarshitaPatel",
"BasantTiwari"
] | 10.1155/2022/9107430
10.1016/j.neucom.2012.02.042
10.1007/s00521-014-1567-3
10.1016/j.jvcir.2019.05.016
10.1007/s00521-020-05204-y
10.1007/s10586-021-03282-8
10.1007/s11063-012-9253-x
10.3390/sym11010001
10.1007/s12559-014-9259-y
10.1016/j.neucom.2007.02.009
10.1109/UT.2017.7890275
10.1109/tgrs.2017.2743102
10.1016/j.a... |
CAD systems for COVID-19 diagnosis and disease stage classification by segmentation of infected regions from CT images. | Here propose a computer-aided diagnosis (CAD) system to differentiate COVID-19 (the coronavirus disease of 2019) patients from normal cases, as well as to perform infection region segmentation along with infection severity estimation using computed tomography (CT) images. The developed system facilitates timely adminis... | BMC bioinformatics | 2022-07-07T00:00:00 | [
"Mohammad HAlshayeji",
"SilpaChandraBhasi Sindhu",
"Sa'edAbed"
] | 10.1186/s12859-022-04818-4
10.1186/s12859-021-04083-x
10.1016/j.patrec.2020.10.001
10.1007/978-3-030-01234-2_49
10.1007/s11042-022-12608-6
10.1016/j.imu.2020.100427
10.1007/s10916-020-01562-1
10.1038/s41598-020-79139-8
10.1038/s41598-019-56847-4
10.1016/j.bbe.2021.05.013
10.1038/s41598-020-79139-8
10.1371/journal.pone.... |
FWLICM-Deep Learning: Fuzzy Weighted Local Information C-Means Clustering-Based Lung Lobe Segmentation with Deep Learning for COVID-19 Detection. | Coronavirus (COVID-19) creates an extensive range of respiratory contagions, and it is a kind of ribonucleic acid (RNA) virus, which affects both animals and humans. Moreover, COVID-19 is a new disease, which produces contamination in upper respiration alterritory and lungs. The new COVID is a rapidly spreading pathoge... | Journal of digital imaging | 2022-07-06T00:00:00 | [
"RRajeswari",
"VeerrajuGampala",
"BalajeeMaram",
"RCristin"
] | 10.1007/s10278-022-00667-y
10.1016/j.compbiomed.2020.103805
10.1016/j.cmpb.2020.105581
10.1016/j.compbiomed.2020.103792
10.1056/NEJMc2001468
10.1007/s12098-020-03263-6
10.1016/S0140-6736(20)30522-5
10.1038/s41368-020-0075-9
10.1148/radiol.2020200490
10.32098/mltj.01.2016.06
10.1053/j.jfas.2020.11.003
10.1016/j.media.20... |
Self-evolving vision transformer for chest X-ray diagnosis through knowledge distillation. | Although deep learning-based computer-aided diagnosis systems have recently achieved expert-level performance, developing a robust model requires large, high-quality data with annotations that are expensive to obtain. This situation poses a conundrum that annually-collected chest x-rays cannot be utilized due to the ab... | Nature communications | 2022-07-06T00:00:00 | [
"SangjoonPark",
"GwanghyunKim",
"YujinOh",
"Joon BeomSeo",
"Sang MinLee",
"Jin HwanKim",
"SungjunMoon",
"Jae-KwangLim",
"Chang MinPark",
"Jong ChulYe"
] | 10.1038/s41467-022-31514-x
10.1001/jama.2016.17216
10.1038/s41591-018-0107-6
10.1038/s41591-018-0029-3
10.1016/j.jacr.2017.12.028
10.1186/s41747-018-0061-6
10.1148/radiol.2017162326
10.1038/s41598-019-42557-4
10.1371/journal.pone.0221339
10.1016/S2589-7500(21)00116-3
10.2174/1573405617666210127154257
10.1016/j.media.20... |
Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographs. | Coronavirus disease 2019 (COVID-19) is a pandemic disease. Fast and accurate diagnosis of COVID-19 from chest radiography may enable more efficient allocation of scarce medical resources and hence improved patient outcomes. Deep learning classification of chest radiographs may be a plausible step towards this. We hypot... | Quantitative imaging in medicine and surgery | 2022-07-06T00:00:00 | [
"Ngo Fung DanielLam",
"HongfeiSun",
"LimingSong",
"DongrongYang",
"ShaohuaZhi",
"GeRen",
"Pak HeiChou",
"Shiu Bun NelsonWan",
"Man Fung EstherWong",
"King KwongChan",
"Hoi Ching HaileyTsang",
"Feng-Ming SpringKong",
"Yì Xiáng JWáng",
"JingQin",
"Lawrence Wing ChiChan",
"MichaelYing",
... | 10.21037/qims-21-791
10.1016/S0140-6736(20)30183-5
10.1016/S2213-2600(20)30076-X
10.2807/1560-7917.ES.2021.26.24.2100509
10.1016/S0140-6736(21)01358-1
10.1056/NEJMoa2002032
10.1148/radiol.2020200642
10.1016/j.radi.2020.10.018
10.1007/s11263-015-0816-y
10.1155/2018/7068349
10.1038/s41598-020-76550-z
10.1007/s10489-020-0... |
Multi-branch fusion auxiliary learning for the detection of pneumonia from chest X-ray images. | Lung infections caused by bacteria and viruses are infectious and require timely screening and isolation, and different types of pneumonia require different treatment plans. Therefore, finding a rapid and accurate screening method for lung infections is critical. To achieve this goal, we proposed a multi-branch fusion ... | Computers in biology and medicine | 2022-07-03T00:00:00 | [
"JiaLiu",
"JingQi",
"WeiChen",
"YongjianNian"
] | 10.1016/j.compbiomed.2022.105732
10.1109/TMI.2020.3040950
10.1128/jcm.02589-20
10.1186/s13054-015-1083-6
10.1002/jmv.25674
10.2807/1560-7917.es.2020.25.3.2000045
10.1148/radiol.2020200432
10.1148/radiol.2020200241
10.1016/j.chest.2020.04.003
10.1148/radiol.2020200343
10.1016/j.clinimag.2020.11.004
10.1148/rg.2018170048... |
Multi-center validation of an artificial intelligence system for detection of COVID-19 on chest radiographs in symptomatic patients. | While chest radiograph (CXR) is the first-line imaging investigation in patients with respiratory symptoms, differentiating COVID-19 from other respiratory infections on CXR remains challenging. We developed and validated an AI system for COVID-19 detection on presenting CXR.
A deep learning model (RadGenX), trained on... | European radiology | 2022-07-03T00:00:00 | [
"Michael DKuo",
"Keith W HChiu",
"David SWang",
"Anna RitaLarici",
"DmytroPoplavskiy",
"AdeleValentini",
"AlessandroNapoli",
"AndreaBorghesi",
"GuidoLigabue",
"Xin Hao BFang",
"Hing Ki CWong",
"SailongZhang",
"John RHunter",
"AbeerMousa",
"AmatoInfante",
"LorenzoElia",
"SalvatoreGole... | 10.1007/s00330-022-08969-z
10.1016/S1473-3099(20)30457-6
10.1001/jamanetworkopen.2020.37067
10.1016/S2468-2667(20)30308-X
10.1056/NEJMp2025631
10.1148/radiol.2020200432
10.1148/radiol.2020201365
10.1038/s41598-020-76550-z
10.1148/radiol.2020203511
10.1109/TMI.2020.2993291
10.1016/j.patrec.2020.09.010
10.1155/2020/88890... |
Explainable deep learning algorithm for distinguishing incomplete Kawasaki disease by coronary artery lesions on echocardiographic imaging. | Incomplete Kawasaki disease (KD) has often been misdiagnosed due to a lack of the clinical manifestations of classic KD. However, it is associated with a markedly higher prevalence of coronary artery lesions. Identifying coronary artery lesions by echocardiography is important for the timely diagnosis of and favorable ... | Computer methods and programs in biomedicine | 2022-07-01T00:00:00 | [
"HaeyunLee",
"YongsoonEun",
"Jae YounHwang",
"Lucy YoungminEun"
] | 10.1016/j.cmpb.2022.106970 |
CVD-HNet: Classifying Pneumonia and COVID-19 in Chest X-ray Images Using Deep Network. | The use of computer-assisted analysis to improve image interpretation has been a long-standing challenge in the medical imaging industry. In terms of image comprehension, Continuous advances in AI (Artificial Intelligence), predominantly in DL (Deep Learning) techniques, are supporting in the classification, Detection,... | Wireless personal communications | 2022-06-28T00:00:00 | [
"SSuganyadevi",
"VSeethalakshmi"
] | 10.1007/s11277-022-09864-y
10.1183/13993003.00775-2020
10.1038/s41598-020-76282-0
10.1109/ACCESS.2020.3005510
10.1007/s13246-020-00865-4
10.1007/s40846-020-00529-4
10.1016/j.cmpb.2020.105581
10.1109/TMI.2020.2993291
10.1016/j.cmpb.2020.105608
10.1016/j.pdpdt.2021.102473
10.1038/s42003-020-01535-7
10.1109/RBME.2020.2990... |
Learning deep neural networks' architectures using differential evolution. Case study: Medical imaging processing. | The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and obstetric care landscapes have been distorted. Delaying cancer diagnosis or maternal-fetal monitoring increased the number of preventable deaths or pregnancy complications. One solution is using Artificial Intelligence to help the medica... | Computers in biology and medicine | 2022-06-26T00:00:00 | [
"SmarandaBelciug"
] | 10.1016/j.compbiomed.2022.105623
10.1159/000508254
10.3390/jcm9113749
10.1016/S2214-109X(21)00079-6
10.1111/jgh15325
10.1136/bmjpo-2020-000859
10.5281/zenodo.3904280
10.1002/uog.20945
10.1002/uog.20796
10.1109/ISBI.2019.8759377
10.1103/PhysRevE.101.052604
10.1038/s41467-021-26568-2
10.1146/annurev-conmatphys-031119-050... |
Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0. | COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesion localization.
ology: The propo... | Computers in biology and medicine | 2022-06-26T00:00:00 | [
"MohitAgarwal",
"SushantAgarwal",
"LucaSaba",
"Gian LucaChabert",
"SuneetGupta",
"AlessandroCarriero",
"AlessioPasche",
"PietroDanna",
"ArminMehmedovic",
"GavinoFaa",
"SaurabhShrivastava",
"KanishkaJain",
"HarshJain",
"TanayJujaray",
"Inder MSingh",
"MonikaTurk",
"Paramjit SChadha",
... | 10.1016/j.compbiomed.2022.105571
10.1002/jmv.25996
10.1002/jmv.25855
10.23736/S0392-9590.21.04771-4 |
Disease Localization and Severity Assessment in Chest X-Ray Images using Multi-Stage Superpixels Classification. | Chest X-ray (CXR) is a non-invasive imaging modality used in the prognosis and management of chronic lung disorders like tuberculosis (TB), pneumonia, coronavirus disease (COVID-19), etc. The radiomic features associated with different disease manifestations assist in detection, localization, and grading the severity o... | Computer methods and programs in biomedicine | 2022-06-25T00:00:00 | [
"Tej BahadurChandra",
"Bikesh KumarSingh",
"DeepakJain"
] | 10.1016/j.cmpb.2022.106947
10.1016/j.media.2020.101847
10.1016/j.media.2020.101846
10.1016/j.eswa.2020.113514
10.1016/j.measurement.2019.05.076
10.1016/j.eswa.2020.113909
10.1016/j.media.2021.102046
10.1016/j.patcog.2020.107613
10.1016/j.media.2018.12.007
10.1007/s10916-019-1222-8
10.1109/ICPC2T48082.2020.9071445
10.11... |
Lung Sonography in Critical Care Medicine. | During the last five decades, lung sonography has developed into a core competency of intensive care medicine. It is a highly accurate bedside tool, with clear diagnostic criteria for most causes of respiratory failure (pneumothorax, pulmonary edema, pneumonia, pulmonary embolism, chronic obstructive pulmonary disease,... | Diagnostics (Basel, Switzerland) | 2022-06-25T00:00:00 | [
"RobertBreitkopf",
"BenediktTreml",
"SasaRajsic"
] | 10.3390/diagnostics12061405
10.1007/s00134-015-3952-5
10.1186/s13089-017-0059-y
10.1016/S2213-2600(14)70135-3
10.1378/chest.14-2608
10.1097/MD.0000000000005713
10.1186/cc13016
10.1590/S1516-31802010000200009
10.1097/CCM.0000000000003129
10.1097/CCM.0b013e31824e68ae
10.3760/CMA.J.ISSN.2095-4352.2015.07.008
10.1007/s0013... |
Novel COVID-19 Diagnosis Delivery App Using Computed Tomography Images Analyzed with Saliency-Preprocessing and Deep Learning. | This app project was aimed to remotely deliver diagnoses and disease-progression information to COVID-19 patients to help minimize risk during this and future pandemics. Data collected from chest computed tomography (CT) scans of COVID-19-infected patients were shared through the app. In this article, we focused on ima... | Tomography (Ann Arbor, Mich.) | 2022-06-24T00:00:00 | [
"SantiagoTello-Mijares",
"FomuyWoo"
] | 10.3390/tomography8030134
10.1016/j.radi.2020.05.012
10.1148/radiol.2020201160
10.1007/s00330-020-06955-x
10.1148/radiol.2020200343
10.2214/AJR.20.22976
10.1016/j.diii.2020.03.014
10.1016/j.ejrad.2020.108941
10.5152/dir.2020.20144
10.1148/radiol.2020200230
10.1007/s00330-020-06976-6
10.1056/NEJMoa2002032
10.1111/jgh.15... |
Convolutional neural network based CT scan classification method for COVID-19 test validation. | Given the novel corona virus discovered in Wuhan, China, in December 2019, due to the high false-negative rate of RT-PCR and the time-consuming to obtain the results, research has proved that computed tomography (CT) has become an auxiliary One of the essential means of diagnosis and treatment of new corona virus pneum... | Smart health (Amsterdam, Netherlands) | 2022-06-21T00:00:00 | [
"MukeshSoni",
"Ajay KumarSingh",
"K SureshBabu",
"SumitKumar",
"AkhileshKumar",
"ShwetaSingh"
] | 10.1016/j.smhl.2022.100296
10.2174/1573405617666210215143503
10.1108/WJE-12-2020-0631
10.1109/ICAS49788.2021.9551169
10.1108/WJE-09-2020-0450
10.1109/JBHI.2021.3060035
10.1109/ASYU52992.2021.9598993
10.1109/ACCESS.2020.3005510
10.1109/JBHI.2020.3042523
10.1155/2021/9293877
10.1109/JBHI.2021.3051470
10.1109/ESCI50559.20... |
Improved Analysis of COVID-19 Influenced Pneumonia from the Chest X-Rays Using Fine-Tuned Residual Networks. | COVID-19 has remained a threat to world life despite a recent reduction in cases. There is still a possibility that the virus will evolve and become more contagious. If such a situation occurs, the resulting calamity will be worse than in the past if we act irresponsibly. COVID-19 must be widely screened and recognized... | Computational intelligence and neuroscience | 2022-06-21T00:00:00 | [
"AmelKsibi",
"MohammedZakariah",
"ManelAyadi",
"HelaElmannai",
"Prashant KumarShukla",
"HalifaAwal",
"MoniaHamdi"
] | 10.1155/2022/9414567
10.1016/s0140-6736(20)30183-5
10.1001/jama.2020.3786
10.2807/1560-7917.ES.2020.25.3.2000045
10.3201/eid2606.200301
10.1038/s42256-021-00338-7
10.5114/pjr.2020.100788
10.1148/radiol.2020200432
10.1148/radiol.2020200343
10.1016/j.media.2020.101794
10.1146/annurev.bioeng.8.061505.095802
10.1093/bib/bb... |
Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review. | Research on the diagnosis of COVID-19 using lung images is limited by the scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis and data augmentation. GANs have been explored for data augmentation to enhance the performance of artificial intelligence (AI) methods for the diagnosis o... | JMIR medical informatics | 2022-06-17T00:00:00 | [
"HazratAli",
"ZubairShah"
] | 10.2196/37365
10.1016/S1473-3099(20)30235-8
10.1016/S1473-3099(20)30235-8
10.1002/jmv.25786
10.2196/20756
10.3389/fmed.2021.704256
10.3389/fmed.2021.704256
10.1109/access.2020.3010287
10.1152/physiolgenomics.00029.2020
10.1109/tai.2020.3020521
10.1109/access.2020.3023495
10.1007/s10916-018-1072-9
10.1016/j.media.2019.1... |
Automated Multi-View Multi-Modal Assessment of COVID-19 Patients Using Reciprocal Attention and Biomedical Transform. | Automated severity assessment of coronavirus disease 2019 (COVID-19) patients can help rationally allocate medical resources and improve patients' survival rates. The existing methods conduct severity assessment tasks mainly on a unitary modal and single view, which is appropriate to exclude potential interactive infor... | Frontiers in public health | 2022-06-14T00:00:00 | [
"YanhanLi",
"HongyunZhao",
"TianGan",
"YangLiu",
"LianZou",
"TingXu",
"XuanChen",
"CienFan",
"MengWu"
] | 10.3389/fpubh.2022.886958
10.1056/NEJMoa2001017
10.1056/NEJMoa2001191
10.1148/radiol.2020200642
10.1148/ryct.2020200034
10.1016/j.compbiomed.2021.104721
10.1016/j.advms.2020.06.005
10.1007/s10439-015-1495-0
10.1016/S2213-2600(20)30120-X
10.1007/978-3-030-32245-8_64
10.1016/j.compmedimag.2019.101688
10.1007/s00330-019-0... |
A Deep Learning Model for Diagnosing COVID-19 and Pneumonia through X-ray. | The new global pandemic caused by the 2019 novel coronavirus (COVID-19), novel coronavirus pneumonia, has spread rapidly around the world, causing enormous damage to daily life, public health security, and the global economy. Early detection and treatment of COVID-19 infected patients are critical to prevent the furthe... | Current medical imaging | 2022-06-14T00:00:00 | [
"XiangbinLiu",
"WenqianWu",
"JerryChun-Wei Lin",
"ShuaiLiu"
] | 10.2174/1573405618666220610093740 |
The Pitfalls of Using Open Data to Develop Deep Learning Solutions for COVID-19 Detection in Chest X-Rays. | Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to hospital data, the AI community relies heavily on public data comprising numerous data sources. Model performance results have been exceptional when training and testing o... | Studies in health technology and informatics | 2022-06-09T00:00:00 | [
"RachaelHarkness",
"GeoffHall",
"Alejandro FFrangi",
"NishantRavikumar",
"KieranZucker"
] | 10.3233/SHTI220164 |
Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care? | The aim of the study was to predict the probability of intensive care unit (ICU) care for inpatient COVID-19 cases using clinical and artificial intelligence segmentation-based volumetric and CT-radiomics parameters on admission.
Twenty-eight clinical/laboratory features, 21 volumetric parameters, and 74 radiomics para... | BMC medical imaging | 2022-06-08T00:00:00 | [
"MutluGülbay",
"AliyeBaştuğ",
"ErdemÖzkan",
"Büşra YüceÖztürk",
"Bökebatur Ahmet RaşitMendi",
"HürremBodur"
] | 10.1186/s12880-022-00833-2
10.1371/journal.pone.0245272
10.1111/joim.13091
10.4266/acc.2020.00381
10.1371/journal.pone.0243709
10.1093/cid/ciaa443
10.1001/jamainternmed.2020.2033
10.1093/cid/ciaa414
10.1186/s40560-021-00527-x
10.7150/ijms.48281
10.5114/pjr.2020.98009
10.7150/thno.46465
10.1148/radiol.2015151169
10.1038... |
Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT. | The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performan... | Scientific reports | 2022-06-08T00:00:00 | [
"DavidBermejo-Peláez",
"RaúlSan José Estépar",
"MaríaFernández-Velilla",
"CarmeloPalacios Miras",
"GuillermoGallardo Madueño",
"MarianaBenegas",
"CarolinaGotera Rivera",
"SandraCuerpo",
"MiguelLuengo-Oroz",
"JacoboSellarés",
"MarceloSánchez",
"GorkaBastarrika",
"GermanPeces Barba",
"Luis M... | 10.1038/s41598-022-13298-8
10.1001/jama.2020.1585
10.1016/S0140-6736(20)30566-3
10.1136/thoraxjnl-2020-216001
10.2214/AJR.20.22976
10.1148/radiol.2020201754
10.1148/ryai.2020200098
10.1016/j.media.2020.101860
10.1038/s41598-021-90991-0
10.1148/radiol.2020200905
10.1038/s41746-021-00446-z
10.1038/s41598-021-84561-7
10.1... |
Towards an effective model for lung disease classification: Using Dense Capsule Nets for early classification of lung diseases. | Machine Learning and computer vision have been the frontiers of the war against the COVID-19 Pandemic. Radiology has vastly improved the diagnosis of diseases, especially lung diseases, through the early assessment of key disease factors. Chest X-rays have thus become among the commonly used radiological tests to detec... | Applied soft computing | 2022-06-07T00:00:00 | [
"FaizanKarim",
"Munam AliShah",
"Hasan AliKhattak",
"ZoobiaAmeer",
"UmarShoaib",
"Hafiz TayyabRauf",
"FadiAl-Turjman"
] | 10.1016/j.asoc.2022.109077 |
Prior-aware autoencoders for lung pathology segmentation. | Segmentation of lung pathology in Computed Tomography (CT) images is of great importance for lung disease screening. However, the presence of different types of lung pathologies with a wide range of heterogeneities in size, shape, location, and texture, on one side, and their visual similarity with respect to surroundi... | Medical image analysis | 2022-06-03T00:00:00 | [
"MehdiAstaraki",
"ÖrjanSmedby",
"ChunliangWang"
] | 10.1016/j.media.2022.102491 |
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