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32804639 | 10.1109/MPULS.2020.3008354 | Yes | null | 32,804,639 | 2,020 | 2020-08-18 | Journal Article | Peer reviewed (PubMed) | 1 | ai-driven covid-19 tools to interpret quantify lung images | Qualitative interpretation is a good thing when it comes to reading lung images in the fight against coronavirus 2019 disease (COVID-19), but quantitative analysis makes radiology reporting much more comprehensive. To that end, several research groups have begun looking to artificial intelligence (AI) as a tool for rea... | 63 | COVID-19 | 5 | IEEE Pulse | Other Topics | 0.000004 | 49.752 | 0.000003 | 185 | 0 | N.A. | Review | Multimodal |
10.1101/2020.08.20.20178723 | 10.1101/2020.08.20.20178723 | Yes | null | null | 2,020 | 2020-08-23 | Preprint | medRxiv | 0 | automatic analysis system of covid-19 radiographic lung images (xraycovidetector) | COVID-19 is a pandemic infectious disease caused by the SARS-CoV-2 virus, having reached more than 210 countries and territories. It produces symptoms such as fever, dry cough, dyspnea, fatigue, pneumonia, and radiological manifestations. The most common reported RX and CT findings include lung consolidation and ground... | 93 | COVID-19;Communicable Diseases;Cough;Dyspnea;Fatigue;Fever;Pneumonia | null | null | Specificity;Communicable Diseases;Eyeglasses | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
32703538 | 10.1067/j.cpradiol.2020.06.009 | Yes | PMC7320858 | 32,703,538 | 2,020 | 2020-07-25 | Journal Article;Review | Peer reviewed (PubMed) | 1 | current landscape of imaging and the potential role for artificial intelligence in the management of covid-19 | The clinical management of COVID-19 is challenging. Medical imaging plays a critical role in the early detection, clinical monitoring and outcomes assessment of this disease. Chest x-ray radiography and computed tomography) are the standard imaging modalities used for the structural assessment of the disease status, wh... | 100 | COVID-19 | 8 | Curr Probl Diagn Radiol | Health Care;Other Topics | 0.000002 | 17.928 | 0.000001 | 53 | 0 | N.A. | Review | Multimodal |
10.1101/2020.04.21.20072637 | 10.1101/2020.04.21.20072637 | Yes | null | null | 2,020 | 2020-04-25 | Preprint | medRxiv | 0 | research on cnn-based models optimized by genetic algorithm and application in the diagnosis of pneumonia and covid-19 | In this research, an optimized deep learning method was proposed to explore the possibility and practicality of neural network applications in medical imaging. The method was used to achieve the goal of judging common pneumonia and even COVID-19 more effectively. Where, the genetic algorithm was taken advantage to opti... | 103 | COVID-19;Pneumonia | null | null | Neural Networks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2003.10304 | null | Yes | null | null | 2,020 | 2020-03-23 | Preprint | arXiv | 0 | attention u-net based adversarial architectures for chest x-ray lung segmentation | Chest X-ray is the most common test among medical imaging modalities. It is applied for detection and differentiation of, among others, lung cancer, tuberculosis, and pneumonia, the last with importance due to the COVID-19 disease. Integrating computer-aided detection methods into the radiologist diagnostic pipeline, g... | 112 | COVID-19;Lung Cancer;Pneumonia;Tuberculosis | null | null | Art;Architecture;Lung Diseases | null | null | null | null | null | External | Segmentation-only | X-Ray |
2007.09695 | null | Yes | null | null | 2,020 | 2020-07-19 | Preprint | arXiv | 0 | using deep convolutional neural networks to diagnose covid-19 from chest x-ray images | The COVID-19 epidemic has become a major safety and health threat worldwide. Imaging diagnosis is one of the most effective ways to screen COVID-19. This project utilizes several open-source or public datasets to present an open-source dataset of COVID-19 CXRs, named COVID-19-CXR-Dataset, and introduces a deep convolut... | 115 | COVID-19 | null | null | Research Personnel;Neural Networks | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32396075 | 10.1109/TMI.2020.2993291 | Yes | null | 32,396,075 | 2,020 | 2020-05-13 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning covid-19 features on cxr using limited training data sets | Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-ray (CXR) image for COVID-19 diagnosis and patient triage is becoming important. Unfortunately, due to the emergent nature of the COVID-19 pandemic, a systematic collection of CXR data set for deep neural network training is di... | 116 | COVID-19;COVID-19 Pandemic | 298 | IEEE Trans Med Imaging | Coronavirus Infections;Art;Algorithms;Map | 0.000007 | 174.592 | 0.00001 | 464 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.12.14.20248158 | 10.1101/2020.12.14.20248158 | Yes | null | null | 2,020 | 2020-12-16 | Preprint | medRxiv | 0 | transfer learning for covid-19 pneumonia detection and classification in chest x-ray images | We introduce a deep learning framework that can detect COVID-19 pneumonia in thoracic radiographs, as well as differentiate it from bacterial pneumonia infection. Deep classification models, such as convolutional neural networks (CNNs), require large-scale datasets in order to be trained and perform properly. Since the... | 124 | COVID-19;Infections;Pneumonia;Pneumonia, Bacterial;Pneumonia, Viral | null | null | Transfer Learning;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32589673 | 10.1371/journal.pone.0235187 | Yes | PMC7319603 | 32,589,673 | 2,020 | 2020-06-27 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | new machine learning method for image-based diagnosis of covid-19 | COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. In this paper, a new ML-method proposed to classify the chest x-ray images into two cla... | 125 | COVID-19 | 106 | PLoS One | Other Topics | 0.000005 | 71.36 | 0.000004 | 204 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2012.15442 | null | Yes | null | null | 2,020 | 2020-12-30 | Preprint | arXiv | 0 | survey of the detection and classification of pulmonary lesions via ct and x-ray | In recent years, the prevalence of several pulmonary diseases, especially the coronavirus disease 2019 (COVID-19) pandemic, has attracted worldwide attention. These diseases can be effectively diagnosed and treated with the help of lung imaging. With the development of deep learning technology and the emergence of many... | 125 | COVID-19;COVID-19 Pandemic;Lung Diseases;Pneumonia | null | null | Other Topics | null | null | null | null | null | N.A. | Review | Multimodal |
2010.04936 | null | Yes | null | null | 2,020 | 2020-10-10 | Preprint | arXiv | 0 | an empirical study on detecting covid-19 in chest x-ray images using deep learning based methods | Spreading of COVID-19 virus has increased the efforts to provide testing kits. Not only the preparation of these kits had been hard, rare, and expensive but also using them is another issue. Results have shown that these kits take some crucial time to recognize the virus, in addition to the fact that they encounter wit... | 126 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33769939 | 10.1109/JBHI.2021.3069169 | Yes | PMC8545163 | 33,769,939 | 2,021 | 2021-03-27 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19 in cxr: from detection and severity scoring to patient disease monitoring | This work estimates the severity of pneumonia in COVID-19 patients and reports the findings of a longitudinal study of disease progression. It presents a deep learning model for simultaneous detection and localization of pneumonia in chest Xray (CXR) images, which is shown to generalize to COVID-19 pneumonia. The local... | 129 | COVID-19;Disease Progression;Pneumonia | 23 | IEEE J Biomed Health Inform | Map;Cone-Beam Computed Tomography | 0.000001 | 20.76 | 0.000001 | 51 | 0 | External | 3. Monitoring/Severity assessment | X-Ray |
2004.02640 | null | Yes | null | null | 2,020 | 2020-04-06 | Preprint | arXiv | 0 | coronavirus detection and analysis on chest ct with deep learning | The outbreak of the novel coronavirus, officially declared a global pandemic, has a severe impact on our daily lives. As of this writing there are approximately 197,188 confirmed cases of which 80,881 are in "Mainland China" with 7,949 deaths, a mortality rate of 3.4%. In order to support radiologists in this overwhelm... | 130 | COVID-19;Death | null | null | Disease Outbreaks;Radiologists;Other Topics;Cluster Analysis | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
10.1101/2020.05.10.20097063 | 10.1101/2020.05.10.20097063 | Yes | null | null | 2,020 | 2020-05-14 | Preprint | medRxiv | 0 | automatic detection of covid-19 infection from chest x-ray using deep learning | COVID-19 infection has created a panic across the globe in recent times. Early detection of COVID-19 infection can save many lives in the prevailing situation. This virus affects the respiratory system of a person and creates white patchy shadows in the lungs. Deep learning is one of the most effective Artificial Intel... | 134 | COVID-19;Infections | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
34373554 | 10.1038/s41598-021-95680-6 | Yes | PMC8352869 | 34,373,554 | 2,021 | 2021-08-11 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | explainable dcnn based chest x-ray image analysis and classification for covid-19 pneumonia detection | To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients based on chest X-ray... | 137 | COVID-19;Pneumonia | 9 | Sci Rep | Sensitivity and Specificity;Neural Networks | 0.000002 | 93.8 | 0.000006 | 205 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.06.07.20124594 | 10.1101/2020.06.07.20124594 | Yes | null | null | 2,020 | 2020-06-08 | Preprint | medRxiv | 0 | early detection of coronavirus cases using chest x-ray images employing machine learning and deep learning approaches | This study aims to investigate if applying machine learning and deep learning approaches on chest X-ray images can detect cases of coronavirus. The chest X-ray datasets were obtained from Kaggle and Github and pre-processed into a single dataset using random sampling. We applied several machine learning and deep learni... | 140 | COVID-19 | null | null | Transfer Learning;Area under Curve | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32983909 | 10.1016/j.matpr.2020.09.352 | Yes | PMC7508494 | 32,983,909 | 2,020 | 2020-09-29 | Journal Article | Peer reviewed (PubMed) | 1 | machine learning and image analysis applications in the fight against covid-19 pandemic: datasets research directions challenges and opportunities | COVID-19 pandemic has become the most devastating disease of the current century and spread over 216 countries around the world. The disease is spreading through outbreaks despite the availability of modern sophisticated medical treatment. Machine Learning and Image Analysis research has been making great progress in m... | 141 | COVID-19 Pandemic | 5 | Mater Today Proc | Health Care;Transfer Learning;Research Personnel;Disease Outbreaks;Risk Factors | 0.000002 | 36.208 | 0.000003 | 90 | 0 | N.A. | Review | X-Ray |
2004.12786 | null | Yes | null | null | 2,020 | 2020-04-30 | Preprint | arXiv | 0 | a cascaded learning strategy for robust covid-19 pneumonia chest x-ray screening | We introduce a comprehensive screening platform for the COVID-19 (a.k.a., SARS-CoV-2) pneumonia. The proposed AI-based system works on chest x-ray (CXR) images to predict whether a patient is infected with the COVID-19 disease. Although the recent international joint effort on making the availability of all sorts of op... | 142 | COVID-19;Pneumonia | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33972584 | 10.1038/s41598-021-88807-2 | Yes | PMC8110795 | 33,972,584 | 2,021 | 2021-05-12 | Journal Article;Research Support, N.I.H., Extramural;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | covid-classifier: an automated machine learning model to assist in the diagnosis of covid-19 infection in chest x-ray images | Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients with pneumonia. However, the similarity between features of CXR images of COVID-19 and pneumonia caused by other infections makes the differential diagnosis by radiologists challenging. We hypothesized that machine learni... | 143 | COVID-19;Infections;Pneumonia | 56 | Sci Rep | Reproducibility of Results;ROC Curve | 0.000002 | 49.52 | 0.000003 | 112 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2010.12967 | null | Yes | null | null | 2,020 | 2020-10-24 | Preprint | arXiv | 0 | automated triage of covid-19 from various lung abnormalities using chest ct features | The outbreak of COVID-19 has lead to a global effort to decelerate the pandemic spread. For this purpose chest computed-tomography (CT) based screening and diagnosis of COVID-19 suspected patients is utilized, either as a support or replacement to reverse transcription-polymerase chain reaction (RT-PCR) test. In this p... | 144 | COVID-19;Infections;Pneumonia | null | null | Disease Outbreaks;Polymerase Chain Reaction;Area under Curve;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
10.1101/2020.04.27.20081984 | 10.1101/2020.04.27.20081984 | Yes | null | null | 2,020 | 2020-05-03 | Preprint | medRxiv | 0 | distinguishing l and h phenotypes of covid-19 using a single x-ray image | Recent observations have shown that there are two types of COVID-19 response: an H phenotype with high lung elastance and weight, and an L phenotype with low measures1. H-type patients have pneumonia-like thickening of the lungs and require ventilation to survive; L-type patients have clearer lungs that may be injured ... | 144 | COVID-19;Disease Progression;Pneumonia;Respiratory Tract Diseases | null | null | Other Topics | null | null | null | null | null | External | 4. Prognosis/Treatment | X-Ray |
10.1101/2020.08.31.20175828 | 10.1101/2020.08.31.20175828 | Yes | null | null | 2,020 | 2020-09-02 | Preprint | medRxiv | 0 | covid-19 detection from chest x-ray images using deep learning and convolutional neural networks | Accurate and efficient diagnosis of potential COVID-19 patients is vital in the fight against the current pandemic. However, even the gold-standard COVID-19 test, reverse transcription polymerase chain reaction, suffers from a high false negative rate and a turnaround time of up to one week, preventing the infected fro... | 146 | COVID-19 | null | null | Polymerase Chain Reaction;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33100403 | 10.1016/j.patcog.2020.107700 | Yes | PMC7568501 | 33,100,403 | 2,020 | 2020-10-27 | Journal Article | Peer reviewed (PubMed) | 1 | metacovid: a siamese neural network framework with contrastive loss for n-shot diagnosis of covid-19 patients | Various AI functionalities such as pattern recognition and prediction can effectively be used to diagnose (recognize) and predict coronavirus disease 2019 (COVID-19) infections and propose timely response (remedial action) to minimize the spread and impact of the virus. Motivated by this, an AI system based on deep met... | 146 | COVID-19;Infections;Pneumonia | 57 | Pattern Recognit | Other Topics | 0.000003 | 54.8 | 0.000004 | 126 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.05.14.20101972 | 10.1101/2020.05.14.20101972 | Yes | null | null | 2,020 | 2020-10-06 | Preprint | medRxiv | 0 | integration of clinical characteristics lab tests and a deep learning ct scan analysis to predict severity of hospitalized covid-19 patients | The SARS-COV-2 pandemic has put pressure on Intensive Care Units, so that identifying predictors of disease severity is a priority. We collected 58 clinical and biological variables, chest CT scan data (506,341 images), and radiology reports from 1,003 coronavirus-infected patients from two French hospitals. We trained... | 147 | COVID-19 | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
32604588 | 10.3233/SHTI200481 | Yes | null | 32,604,588 | 2,020 | 2020-07-02 | Journal Article | Peer reviewed (PubMed) | 1 | setting up an easy-to-use machine learning pipeline for medical decision support: a case study for covid-19 diagnosis based on deep learning with ct scans | Coronavirus disease (COVID-19) constitutes an ongoing global health problem with significant morbidity and mortality. It usually presents characteristic findings on a chest CT scan, which may lead to early detection of the disease. A timely and accurate diagnosis of COVID-19 is the cornerstone for the prompt management... | 148 | COVID-19;Pneumonia | 26 | Stud Health Technol Inform | Other Topics | 0.000005 | 86.376 | 0.000005 | 257 | 0 | External | 2. Detection/Diagnosis | CT |
35431611 | 10.1007/s11042-022-12156-z | Yes | PMC8989406 | 35,431,611 | 2,022 | 2022-04-19 | Journal Article | Peer reviewed (PubMed) | 1 | covid-cxnet: detecting covid-19 in frontal chest x-ray images using deep learning | One of the primary clinical observations for screening the novel coronavirus is capturing a chest x-ray image. In most patients, a chest x-ray contains abnormalities, such as consolidation, resulting from COVID-19 viral pneumonia. In this study, research is conducted on efficiently detecting imaging features of this ty... | 149 | COVID-19;Pneumonia;Pneumonia, Viral | 42 | Multimed Tools Appl | Transfer Learning;Other Topics | 0.000001 | 22.6 | 0.000002 | 35 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32796848 | 10.1038/s41467-020-17971-2 | Yes | PMC7429815 | 32,796,848 | 2,020 | 2020-08-17 | Journal Article;Research Support, N.I.H., Intramural;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | artificial intelligence for the detection of covid-19 pneumonia on chest ct using multinational datasets | Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorit... | 150 | COVID-19;Lung Diseases;Pneumonia | 211 | Nat Commun | Coronavirus Infections;COVID-19 Testing | 0.000006 | 139.128 | 0.000008 | 369 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32959234 | 10.1007/s12539-020-00393-5 | Yes | PMC7505483 | 32,959,234 | 2,020 | 2020-09-23 | Journal Article | Peer reviewed (PubMed) | 1 | covid19xraynet: a two-step transfer learning model for the covid-19 detecting problem based on a limited number of chest x-ray images | The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a major pandemic outbreak recently. Various diagnostic technologies have been under active development. The novel coronavirus disease (COVID-19) may induce pulmonary failures, and chest X-ray imaging becomes one of the major c... | 151 | COVID-19;Severe Acute Respiratory Syndrome | 18 | Interdiscip Sci | Radiography;Coronavirus Infections;Transfer Learning;Algorithms;Disease Outbreaks;COVID-19 Testing;Lung;Neural Networks;Tomography | 0.00001 | 298.336 | 0.000016 | 764 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32356760 | 10.1109/RBME.2020.2990959 | Yes | null | 32,356,760 | 2,020 | 2020-05-02 | Journal Article;Review | Peer reviewed (PubMed) | 1 | the role of imaging in the detection and management of covid-19: a review | Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have p... | 153 | COVID-19;Death;Infections;Pneumonia;Severe Acute Respiratory Syndrome | 130 | IEEE Rev Biomed Eng | Magnetic Resonance Imaging;Pneumonia;Lung;Ultrasonography;Tomography;Review | 0.000002 | 77.88 | 0.000004 | 173 | 0 | External | Review | Multimodal |
32536759 | 10.1016/j.chaos.2020.109944 | Yes | PMC7254021 | 32,536,759 | 2,020 | 2020-06-17 | Journal Article | Peer reviewed (PubMed) | 1 | application of deep learning for fast detection of covid-19 in x-rays using ncovnet | Presently, COVID-19 has posed a serious threat to researchers, scientists, health professionals, and administrations around the globe from its detection to its treatment. The whole world is witnessing a lockdown like situation because of COVID-19 pandemic. Persistent efforts are being made by the researchers to obtain ... | 154 | COVID-19;COVID-19 Pandemic | 192 | Chaos Solitons Fractals | Other Topics | 0.000004 | 88.88 | 0.000006 | 210 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32834523 | 10.1007/s00138-020-01101-5 | Yes | PMC7386599 | 32,834,523 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning applications in pulmonary medical imaging: recent updates and insights on covid-19 | Shortly after deep learning algorithms were applied to Image Analysis, and more importantly to medical imaging, their applications increased significantly to become a trend. Likewise, deep learning applications (DL) on pulmonary medical images emerged to achieve remarkable advances leading to promising clinical trials.... | 154 | COVID-19;COVID-19 Pandemic;Cancer;Infections;Lung Diseases | 20 | Mach Vis Appl | Coronavirus Infections;Art;Algorithms;Lung Diseases | 0.000003 | 14.632 | 0.000002 | 39 | 0 | N.A. | Review | Multimodal |
10.1101/2020.04.13.20063479 | 10.1101/2020.04.13.20063479 | Yes | null | null | 2,020 | 2020-04-17 | Preprint | medRxiv | 0 | machine learning analysis of chest ct scan images as a complementary digital test of coronavirus (covid-19) patients | This paper reports on the development and performance of machine learning schemes for the analysis of Chest CT Scan images of Coronavirus COVID-19 patients and demonstrates significant success in efficiently and automatically testing for COVID-19 infection. In particular, an innovative frequency domain algorithm, to be... | 154 | COVID-19;Infections | null | null | Coronavirus Infections;Polymerase Chain Reaction | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
10.1101/2020.10.13.20178483 | 10.1101/2020.10.13.20178483 | Yes | null | null | 2,020 | 2020-10-14 | Preprint | medRxiv | 0 | automated chest radiograph diagnosis: a twofer for tuberculosis and covid-19 | Coronavirus disease (Covid 19) and Tuberculosis (TB) are two challenges the world is facing. TB is a pandemic which has challenged mankind for ages and Covid 19 is a recent onset fast spreading pandemic. We study these two conditions with focus on Artificial Intelligence (AI) based imaging, the role of digital chest x-... | 154 | COVID-19;COVID-19 Pandemic;Tuberculosis | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.05.01.20088211 | 10.1101/2020.05.01.20088211 | Yes | null | null | 2,020 | 2020-06-18 | Preprint | medRxiv | 0 | classification of covid-19 from chest x-ray images using deep convolutional neural networks | The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. A vital step in the combat towards COVID-19 is a successful screening of contaminated patients, with one of the key screening approaches being radiological imaging using chest radiography. This study aime... | 155 | COVID-19;COVID-19 Pandemic;Pneumonia;Pneumonia, Viral | null | null | Transfer Learning;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
2004.03747 | null | Yes | null | null | 2,020 | 2020-04-18 | Preprint | arXiv | 0 | covid_mtnet: covid-19 detection with multi-task deep learning approaches | COVID-19 is currently one the most life-threatening problems around the world. The fast and accurate detection of the COVID-19 infection is essential to identify, take better decisions and ensure treatment for the patients which will help save their lives. In this paper, we propose a fast and efficient way to identify ... | 155 | COVID-19;Infections | null | null | Transfer Learning;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
2007.14318 | null | Yes | null | null | 2,020 | 2020-08-29 | Preprint | arXiv | 0 | covmunet: a multiple loss approach towards detection of covid-19 from chest x-ray | The recent outbreak of COVID-19 has halted the whole world, bringing a devastating effect on public health, global economy, and educational systems. As the vaccine of the virus is still not available, the most effective way to combat the virus is testing and social distancing. Among all other detection techniques, the ... | 156 | COVID-19;Pneumonia | null | null | Public Health;Art;Algorithms;Architecture;Disease Outbreaks | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33208927 | 10.1038/s41551-020-00633-5 | Yes | PMC7723858 | 33,208,927 | 2,020 | 2020-11-20 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | open resource of clinical data from patients with pneumonia for the prediction of covid-19 outcomes via deep learning | Data from patients with coronavirus disease 2019 (COVID-19) are essential for guiding clinical decision making, for furthering the understanding of this viral disease, and for diagnostic modelling. Here, we describe an open resource containing data from 1,521 patients with pneumonia (including COVID-19 pneumonia) consi... | 156 | COVID-19;Pneumonia;Severe Acute Respiratory Syndrome;Virus Diseases | 64 | Nat Biomed Eng | Algorithms;ROC Curve | 0.000003 | 45.216 | 0.000003 | 140 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | CT |
32742318 | 10.3892/etm.2020.8797 | Yes | PMC7388253 | 32,742,318 | 2,020 | 2020-08-04 | Journal Article | Peer reviewed (PubMed) | 1 | interpretable artificial intelligence framework for covid-19 screening on chest x-rays | COVID-19 has led to an unprecedented healthcare crisis with millions of infected people across the globe often pushing infrastructures, healthcare workers and entire economies beyond their limits. The scarcity of testing kits, even in developed countries, has led to extensive research efforts towards alternative soluti... | 156 | COVID-19 | 45 | Exp Ther Med | Health Care;Transfer Learning;Research Personnel;Health;Map | 0.000002 | 22.032 | 0.000002 | 62 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.07.08.20149161 | 10.1101/2020.07.08.20149161 | Yes | null | null | 2,020 | 2020-07-10 | Preprint | medRxiv | 0 | covidpen: a novel covid-19 detection model using chest x-rays and ct scans | The trending global pandemic of COVID-19 is the fastest ever impact which caused people worldwide by severe acute respiratory syndrome (SARS)-driven coronavirus. However, several countries suffer from the shortage of test kits and high false negative rate in PCR test. Enhancing the chest X-ray or CT detection rate beco... | 157 | COVID-19;Severe Acute Respiratory Syndrome | null | null | Transfer Learning;Polymerase Chain Reaction;Tomography;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
33643491 | 10.1007/s13278-021-00731-5 | Yes | PMC7903408 | 33,643,491 | 2,021 | 2021-03-02 | Journal Article | Peer reviewed (PubMed) | 1 | synthesis of covid-19 chest x-rays using unpaired image-to-image translation | Motivated by the lack of publicly available datasets of chest radiographs of positive patients with coronavirus disease 2019 (COVID-19), we build the first-of-its-kind open dataset of synthetic COVID-19 chest X-ray images of high fidelity using an unsupervised domain adaptation approach by leveraging class conditioning... | 157 | COVID-19;COVID-19 Pandemic | 13 | Soc Netw Anal Min | X-Rays;Translations | 0.000001 | 24.6 | 0.000002 | 55 | 0 | External | 5. Post-hoc | X-Ray |
2004.05436 | null | Yes | null | null | 2,020 | 2020-04-11 | Preprint | arXiv | 0 | detection of covid-19 from chest x-ray images using artificial intelligence: an early review | In 2019, the entire world is facing a situation of health emergency due to a newly emerged coronavirus (COVID-19). Almost 196 countries are affected by covid-19, while USA, Italy, China, Spain, Iran, and France have the maximum active cases of COVID-19. The issues, medical and healthcare departments are facing in delay... | 158 | COVID-19;Pneumonia | null | null | Health Care;Other Topics | null | null | null | null | null | External | Review | X-Ray |
32501424 | 10.1016/j.imu.2020.100360 | Yes | PMC7255267 | 32,501,424 | 2,020 | 2020-06-06 | Journal Article | Peer reviewed (PubMed) | 1 | a modified deep convolutional neural network for detecting covid-19 and pneumonia from chest x-ray images based on the concatenation of xception and resnet50v2 | In this paper, we have trained several deep convolutional networks with introduced training techniques for classifying X-ray images into three classes: normal, pneumonia, and COVID-19, based on two open-source datasets. Our data contains 180 X-ray images that belong to persons infected with COVID-19, and we attempted t... | 160 | COVID-19;Pneumonia | 162 | Inform Med Unlocked | Transfer Learning;Other Topics | 0.000007 | 138.352 | 0.000009 | 342 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33961635 | 10.1371/journal.pone.0250952 | Yes | PMC8104381 | 33,961,635 | 2,021 | 2021-05-08 | Journal Article | Peer reviewed (PubMed) | 1 | ai-corona: radiologist-assistant deep learning framework for covid-19 diagnosis in chest ct scans | The development of medical assisting tools based on artificial intelligence advances is essential in the global fight against COVID-19 outbreak and the future of medical systems. In this study, we introduce ai-corona, a radiologist-assistant deep learning framework for COVID-19 infection diagnosis using chest CT scans.... | 160 | COVID-19;Infections;Pneumonia | 23 | PLoS One | Disease Outbreaks;Polymerase Chain Reaction;Radiologists;Other Topics;ROC Curve;Area under Curve | 0.000001 | 35.68 | 0.000002 | 82 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33014121 | 10.1155/2020/9756518 | Yes | PMC7519983 | 33,014,121 | 2,020 | 2020-10-06 | Journal Article;Review | Peer reviewed (PubMed) | 1 | review on diagnosis of covid-19 from chest ct images using artificial intelligence | The COVID-19 diagnostic approach is mainly divided into two broad categories, a laboratory-based and chest radiography approach. The last few months have witnessed a rapid increase in the number of studies use artificial intelligence (AI) techniques to diagnose COVID-19 with chest computed tomography (CT). In this stud... | 161 | COVID-19;Pneumonia | 74 | Comput Math Methods Med | Radiography;Coronavirus Infections;COVID-19 Testing;Sensitivity and Specificity;Neural Networks | 0.000006 | 131.504 | 0.000007 | 392 | 0 | N.A. | Review | CT |
2007.05592 | null | Yes | null | null | 2,020 | 2020-07-05 | Preprint | arXiv | 0 | experiments of federated learning for covid-19 chest x-ray images | AI plays an important role in COVID-19 identification. Computer vision and deep learning techniques can assist in determining COVID-19 infection with Chest X-ray Images. However, for the protection and respect of the privacy of patients, the hospital's specific medical-related data did not allow leakage and sharing wit... | 161 | COVID-19;Infections | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2008.02866 | null | Yes | null | null | 2,020 | 2020-08-15 | Preprint | arXiv | 0 | improving explainability of image classification in scenarios with class overlap: application to covid-19 and pneumonia | Trust in predictions made by machine learning models is increased if the model generalizes well on previously unseen samples and when inference is accompanied by cogent explanations of the reasoning behind predictions. In the image classification domain, generalization can be assessed through accuracy, sensitivity, and... | 163 | COVID-19;Pneumonia | null | null | Other Topics | null | null | null | null | null | External | 5. Post-hoc | X-Ray |
33967656 | 10.1016/j.inffus.2021.04.008 | Yes | PMC8086233 | 33,967,656 | 2,021 | 2021-05-11 | Journal Article | Peer reviewed (PubMed) | 1 | a critic evaluation of methods for covid-19 automatic detection from x-ray images | In this paper, we compare and evaluate different testing protocols used for automatic COVID-19 diagnosis from X-Ray images in the recent literature. We show that similar results can be obtained using X-Ray images that do not contain most of the lungs. We are able to remove the lungs from the images by turning to black ... | 165 | COVID-19 | 63 | Inf Fusion | Black Americans;Research Personnel;Techniques;X-Rays;Dataset;Paper | 0.000002 | 46.68 | 0.000003 | 107 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.05.06.20092874 | 10.1101/2020.05.06.20092874 | Yes | null | null | 2,020 | 2020-05-08 | Preprint | medRxiv | 0 | prognet: covid-19 prognosis using recurrent and convolutional neural networks | , Humanity is facing nowadays a dramatic pandemic episode with the Coronavirus propagation over all continents. The Covid-19 disease is still not well characterized, and many research teams all over the world are working on either therapeutic or vaccination issues. Massive testing is one of the main recommendations. In... | 166 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | 4. Prognosis/Treatment | X-Ray |
10.1101/2020.11.08.20227819 | 10.1101/2020.11.08.20227819 | Yes | null | null | 2,020 | 2020-11-12 | Preprint | medRxiv | 0 | detection of covid-19 disease from chest x-ray images: a deep transfer learning framework | World economy as well as public health have been facing a devastating effect caused by the disease termed as Coronavirus (COVID-19). A significant step of COVID-19 affected patient’s treatment is the faster and accurate detection of the disease which is the motivation of this study. In this paper, implementation of a d... | 168 | COVID-19;Pneumonia, Viral | null | null | Public Health;Transfer Learning | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2004.09750 | null | Yes | null | null | 2,021 | 2021-03-21 | Preprint | arXiv | 0 | miniseg: an extremely minimum network for efficient covid-19 segmentation | The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentation, has attracted much attention. However, the publicly available COVID-19 training data are limited, easily causing overfitting for tradit... | 169 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | Segmentation-only | CT |
32700269 | 10.1007/s11356-020-10133-3 | Yes | PMC7375456 | 32,700,269 | 2,020 | 2020-07-24 | Journal Article | Peer reviewed (PubMed) | 1 | drawing insights from covid-19-infected patients using ct scan images and machine learning techniques: a study on 200 patients | As the whole world is witnessing what novel coronavirus (COVID-19) can do to the mankind, it presents several unique features also. In the absence of specific vaccine for COVID-19, it is essential to detect the disease at an early stage and isolate an infected patient. Till today there is a global shortage of testing l... | 169 | COVID-19;Pneumonia;Pneumonia, Viral | 34 | Environ Sci Pollut Res Int | Coronavirus Infections;Polymerase Chain Reaction | 0.000003 | 44.368 | 0.000003 | 142 | 0 | External | 2. Detection/Diagnosis | CT |
33169050 | 10.1007/s00138-020-01128-8 | Yes | PMC7609373 | 33,169,050 | 2,020 | 2020-11-11 | Journal Article | Peer reviewed (PubMed) | 1 | a five-layer deep convolutional neural network with stochastic pooling for chest ct-based covid-19 diagnosis | Till August 17, 2020, COVID-19 has caused 21.59 million confirmed cases in more than 227 countries and territories, and 26 naval ships. Chest CT is an effective way to detect COVID-19. This study proposed a novel deep learning model that can diagnose COVID-19 on chest CT more accurately and swiftly. Based on traditiona... | 170 | COVID-19 | 32 | Mach Vis Appl | Other Topics | 0.000003 | 31.048 | 0.000003 | 77 | 0 | External | 2. Detection/Diagnosis | CT |
10.1101/2020.12.20.20248582 | 10.1101/2020.12.20.20248582 | Yes | null | null | 2,020 | 2020-12-23 | Preprint | medRxiv | 0 | rapid covid-19 diagnosis using deep learning of the computerized tomography scans | Several studies suggest that COVID-19 may be accompanied by symptoms such as a dry cough, muscle aches, sore throat, and mild to moderate respiratory illness. The symptoms of this disease indicate the fact that COVID-19 causes noticeable negative effects on the lungs. Therefore, considering the health status of the lun... | 170 | Ache;COVID-19;Coronavirus Infections;Cough;Infections;Sore Throat | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
33171345 | 10.1016/j.media.2020.101860 | Yes | PMC7558247 | 33,171,345 | 2,020 | 2020-11-11 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | ai-driven quantification staging and outcome prediction of covid-19 pneumonia | Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around the world rapidly. Computed tomography (CT) imaging has been proven to be an important tool for screening, disease quantification and staging. The latter is of extreme importance for organizational anticipation (availability of intensive care u... | 172 | COVID-19;Pneumonia | 63 | Med Image Anal | Drug;Architecture;Neural Networks | 0.000004 | 49.528 | 0.000004 | 147 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | CT |
2003.10769 | null | Yes | null | null | 2,020 | 2020-03-27 | Preprint | arXiv | 0 | estimating uncertainty and interpretability in deep learning for coronavirus (covid-19) detection | Deep Learning has achieved state of the art performance in medical imaging. However, these methods for disease detection focus exclusively on improving the accuracy of classification or predictions without quantifying uncertainty in a decision. Knowing how much confidence there is in a computer-based medical diagnosis ... | 172 | COVID-19 | null | null | Coronavirus Infections;Art;Health Care | null | null | null | null | null | External | Segmentation-only | X-Ray |
33603047 | 10.1038/s41598-021-83424-5 | Yes | PMC7892869 | 33,603,047 | 2,021 | 2021-02-20 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | assisting scalable diagnosis automatically via ct images in the combat against covid-19 | The pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tom... | 173 | COVID-19;Infections;Pneumonia | 13 | Sci Rep | Polymerase Chain Reaction;Other Topics;Retrospective Studies;Reverse Transcription | 0.000001 | 37.96 | 0.000002 | 89 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32436845 | 10.5152/dir.2019.20294 | Yes | PMC7490030 | 32,436,845 | 2,020 | 2020-05-22 | Journal Article;Review | Peer reviewed (PubMed) | 1 | a review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019 | The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of COVID-19 pneumonia. PubMed, arXiv, medRxiv, and Google scholar were us... | 173 | COVID-19;Pneumonia | 21 | Diagn Interv Radiol | Other Topics | 0.000004 | 82.144 | 0.000004 | 252 | 0 | External | Review | Multimodal |
2008.11639 | null | Yes | null | null | 2,020 | 2020-10-09 | Preprint | arXiv | 0 | a comparison of deep machine learning algorithms in covid-19 disease diagnosis | The aim of the work is to use deep neural network models for solving the problem of image recognition. These days, every human being is threatened by a harmful coronavirus disease, also called COVID-19 disease. The spread of coronavirus affects the economy of many countries in the world. To find COVID-19 patients early... | 173 | COVID-19 | null | null | Neural Networks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33286289 | 10.3390/e22050517 | Yes | PMC7517011 | 33,286,289 | 2,020 | 2020-12-09 | Journal Article | Peer reviewed (PubMed) | 1 | classification of covid-19 coronavirus pneumonia and healthy lungs in ct scans using q-deformed entropy and deep learning features | Many health systems over the world have collapsed due to limited capacity and a dramatic increase of suspected COVID-19 cases. What has emerged is the need for finding an efficient, quick and accurate method to mitigate the overloading of radiologists' efforts to diagnose the suspected cases. This study presents the co... | 173 | COVID-19;Pneumonia | 46 | Entropy (Basel) | Health;Radiologists;Entropy | 0.000002 | 32.96 | 0.000003 | 86 | 0 | External | 2. Detection/Diagnosis | CT |
32971995 | 10.3390/ijerph17186933 | Yes | PMC7557723 | 32,971,995 | 2,020 | 2020-09-26 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | unveiling covid-19 from chest x-ray with deep learning: a hurdles race with small data | The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-19 patients is attracting much interest from both the clinical and the AI community. In this study we provide insights and also raise warnings on what is reasonable to expect by applying deep learning to COVID classifica... | 174 | COVID-19 | 73 | Int J Environ Res Public Health | Coronavirus Infections;Transfer Learning | 0.000003 | 50.928 | 0.000003 | 146 | 0 | External | 2. Detection/Diagnosis | X-Ray |
rs-1396136 | 10.21203/rs.3.rs-1396136/v1 | Yes | null | null | 2,022 | 2022-03-11 | Preprint | Research Square | 0 | exploration of interpretability techniques for deep covid-19 classification using chest x-ray images | The outbreak of COVID-19 has shocked the entire world with its fairly rapid spread and has challenged different sectors. One of the most effective ways to limit its spread is the early and accurate diagnosis of infected patients. Medical imaging such as X-ray and Computed Tomography (CT) combined with the potential of ... | 175 | COVID-19 | null | null | Disease Outbreaks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2003.14363 | null | Yes | null | null | 2,020 | 2020-03-31 | Preprint | arXiv | 0 | automated methods for detection and classification pneumonia based on x-ray images using deep learning | Recently, researchers, specialists, and companies around the world are rolling out deep learning and image processing-based systems that can fastly process hundreds of X-Ray and computed tomography (CT) images to accelerate the diagnosis of pneumonia such as SARS, COVID-19, and aid in its containment. Medical images an... | 175 | COVID-19;Pneumonia | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32760732 | 10.3389/fmed.2020.00427 | Yes | PMC7371960 | 32,760,732 | 2,020 | 2020-08-08 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning-based decision-tree classifier for covid-19 diagnosis from chest x-ray imaging | The global pandemic of coronavirus disease 2019 (COVID-19) has resulted in an increased demand for testing, diagnosis, and treatment. Reverse transcription polymerase chain reaction (RT-PCR) is the definitive test for the diagnosis of COVID-19; however, chest X-ray radiography (CXR) is a fast, effective, and affordable... | 175 | COVID-19;Pneumonia;Tuberculosis | 81 | Front Med (Lausanne) | Pneumonia;Polymerase Chain Reaction;Decision Trees;Reverse Transcription | 0.000005 | 71.832 | 0.000006 | 183 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33980980 | 10.1038/s41746-021-00453-0 | Yes | PMC8115328 | 33,980,980 | 2,021 | 2021-05-14 | Journal Article | Peer reviewed (PubMed) | 1 | an artificial intelligence system for predicting the deterioration of covid-19 patients in the emergency department | During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradien... | 175 | COVID-19;COVID-19 Pandemic | 41 | NPJ Digit Med | Other Topics | 0.000002 | 22.24 | 0.000002 | 48 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | X-Ray |
2007.01108 | null | Yes | null | null | 2,020 | 2020-06-30 | Preprint | arXiv | 0 | evaluation of contemporary convolutional neural network architectures for detecting covid-19 from chest radiographs | Interpreting chest radiograph, a.ka. chest x-ray, images is a necessary and crucial diagnostic tool used by medical professionals to detect and identify many diseases that may plague a patient. Although the images themselves contain a wealth of valuable information, their usefulness may be limited by how well they are ... | 177 | COVID-19;COVID-19 Pandemic;Infections;Plague | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32568679 | 10.1016/j.compbiomed.2020.103805 | Yes | PMC7202857 | 32,568,679 | 2,020 | 2020-06-23 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19 detection using deep learning models to exploit social mimic optimization and structured chest x-ray images using fuzzy color and stacking approaches | Coronavirus causes a wide variety of respiratory infections and it is an RNA-type virus that can infect both humans and animal species. It often causes pneumonia in humans. Artificial intelligence models have been helpful for successful analyses in the biomedical field. In this study, Coronavirus was detected using a d... | 177 | COVID-19;Pneumonia;Respiratory Tract Infections | 197 | Comput Biol Med | Other Topics | 0.000007 | 131.656 | 0.000008 | 355 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2010.09456 | null | Yes | null | null | 2,020 | 2020-10-19 | Preprint | arXiv | 0 | gasnet: weakly-supervised framework for covid-19 lesion segmentation | Segmentation of infected areas in chest CT volumes is of great significance for further diagnosis and treatment of COVID-19 patients. Due to the complex shapes and varied appearances of lesions, a large number of voxel-level labeled samples are generally required to train a lesion segmentation network, which is a main ... | 178 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | Segmentation-only | CT |
10.1101/2020.05.04.20090779 | 10.1101/2020.05.04.20090779 | Yes | null | null | 2,020 | 2020-05-08 | Preprint | medRxiv | 0 | mantiscovid: rapid x-ray chest radiograph and mortality rate evaluation with artificial intelligence for covid-19 | The novel coronavirus pandemic has negative impacts over the health, economy and well-being of the global population. This negative effect is growing with the high spreading rate of the virus. The most critical step to prevent the spreading of the virus is pre-screening and early diagnosis of the individuals. This resu... | 178 | COVID-19;Infections | null | null | Coronavirus Infections;Diagnostic Tests;COVID-19 Testing | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32849861 | 10.1155/2020/8828855 | Yes | PMC7439162 | 32,849,861 | 2,020 | 2020-08-28 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19 deep learning prediction model using publicly available radiologist-adjudicated chest x-ray images as training data: preliminary findings | The key component in deep learning research is the availability of training data sets. With a limited number of publicly available COVID-19 chest X-ray images, the generalization and robustness of deep learning models to detect COVID-19 cases developed based on these images are questionable. We aimed to use thousands o... | 178 | COVID-19 | 46 | Int J Biomed Imaging | Other Topics | 0.000003 | 32.232 | 0.000003 | 85 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32619398 | 10.1080/07391102.2020.1788642 | Yes | null | 32,619,398 | 2,020 | 2020-07-04 | Journal Article | Peer reviewed (PubMed) | 1 | classification of the covid-19 infected patients using densenet201 based deep transfer learning | Deep learning models are widely used in the automatic analysis of radiological images. These techniques can train the weights of networks on large datasets as well as fine tuning the weights of pre-trained networks on small datasets. Due to the small COVID-19 dataset available, the pre-trained neural networks can be us... | 180 | COVID-19 | 174 | J Biomol Struct Dyn | Transfer Learning;Architecture;Neural Networks;Tomography | 0.000006 | 218.76 | 0.000013 | 477 | 0 | External | 2. Detection/Diagnosis | CT |
33363252 | 10.1016/j.imu.2020.100505 | Yes | PMC7752710 | 33,363,252 | 2,020 | 2020-12-29 | Journal Article | Peer reviewed (PubMed) | 1 | emcnet: automated covid-19 diagnosis from x-ray images using convolutional neural network and ensemble of machine learning classifiers | Recently, coronavirus disease (COVID-19) has caused a serious effect on the healthcare system and the overall global economy. Doctors, researchers, and experts are focusing on alternative ways for the rapid detection of COVID-19, such as the development of automatic COVID-19 detection systems. In this paper, an automat... | 180 | COVID-19 | 60 | Inform Med Unlocked | Health Care;Research Personnel;Support Vector Machine;Decision Trees;Random Forest | 0.000005 | 94.64 | 0.000007 | 228 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32337662 | 10.1007/s10096-020-03901-z | Yes | PMC7183816 | 32,337,662 | 2,020 | 2020-04-28 | Journal Article | Peer reviewed (PubMed) | 1 | classification of covid-19 patients from chest ct images using multi-objective differential evolution-based convolutional neural networks | Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR), chest computed tomography (CT) imaging may be a significantly more trustworthy, useful, and rapid technique to classify and evaluate COVID-... | 180 | COVID-19;Infections | 204 | Eur J Clin Microbiol Infect Dis | Coronavirus Infections;COVID-19 Testing;Sensitivity and Specificity;Polymerase Chain Reaction;Neural Networks;Paper;Reverse Transcription | 0.000009 | 202.568 | 0.000013 | 507 | 0 | External | 2. Detection/Diagnosis | CT |
33041409 | 10.1016/j.patrec.2020.10.001 | Yes | PMC7532353 | 33,041,409 | 2,020 | 2020-10-13 | Journal Article | Peer reviewed (PubMed) | 1 | a light cnn for detecting covid-19 from ct scans of the chest | Computer Tomography (CT) imaging of the chest is a valid diagnosis tool to detect COVID-19 promptly and to control the spread of the disease. In this work we propose a light Convolutional Neural Network (CNN) design, based on the model of the SqueezeNet, for the efficient discrimination of COVID-19 CT images with respe... | 180 | COVID-19;Pneumonia | 79 | Pattern Recognit Lett | Other Topics | 0.000002 | 40.264 | 0.000003 | 93 | 0 | External | 2. Detection/Diagnosis | CT |
33440674 | 10.3390/s21020455 | Yes | PMC7828058 | 33,440,674 | 2,021 | 2021-01-15 | Journal Article | Peer reviewed (PubMed) | 1 | explainable covid-19 detection using chest ct scans and deep learning | This paper explores how well deep learning models trained on chest CT images can diagnose COVID-19 infected people in a fast and automated process. To this end, we adopted advanced deep network architectures and proposed a transfer learning strategy using custom-sized input tailored for each deep architecture to achiev... | 181 | COVID-19 | 63 | Sensors (Basel) | Transfer Learning;Algorithms;Architecture;Sensitivity and Specificity;Neural Networks;Tomography | 0.000005 | 201.6 | 0.00001 | 468 | 0 | External | 2. Detection/Diagnosis | CT |
10.1101/2020.11.08.20228080 | 10.1101/2020.11.08.20228080 | Yes | null | null | 2,020 | 2020-11-12 | Preprint | medRxiv | 0 | automatic covid-19 detection from chest radiographic images using convolutional neural network | The global pandemic of the novel coronavirus that started in Wuhan, China has affected more than 2 million people worldwide and caused more than 130,000 tragic deaths. To date, the COVID-19 virus is still spreading and affecting thousands of people. The main problem with testing for COVID-19 is that there are very few ... | 181 | COVID-19;Death | null | null | Polymerase Chain Reaction;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2004.05645 | null | Yes | null | null | 2,020 | 2020-04-12 | Preprint | arXiv | 0 | residual attention u-net for automated multi-class segmentation of covid-19 chest ct images | The novel coronavirus disease 2019 (COVID-19) has been spreading rapidly around the world and caused significant impact on the public health and economy. However, there is still lack of studies on effectively quantifying the lung infection caused by COVID-19. As a basic but challenging task of the diagnostic framework,... | 181 | COVID-19;Infections | null | null | Other Topics | null | null | null | null | null | External | Segmentation-only | CT |
33161334 | 10.1016/j.compbiomed.2020.104092 | Yes | PMC7591316 | 33,161,334 | 2,020 | 2020-11-09 | Journal Article | Peer reviewed (PubMed) | 1 | the importance of standardisation - covid-19 ct and radiograph image data stock for deep learning purpose | With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. The deep learning community concentrates their efforts on exploring if neural networks can potentially support the diagnosis using CT and radiograph images of patients' lungs. The two most popular publi... | 181 | COVID-19;Pneumonia | 5 | Comput Biol Med | Other Topics | 0.000004 | 64.952 | 0.000004 | 195 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32397844 | 10.1080/07391102.2020.1767212 | Yes | PMC7256347 | 32,397,844 | 2,020 | 2020-05-14 | Journal Article | Peer reviewed (PubMed) | 1 | using x-ray images and deep learning for automated detection of coronavirus disease | Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classification system as a speedy elective finding choice to forestall COVID-1... | 181 | COVID-19;Confusion;Death;Pneumonia;Pneumonia, Bacterial | 101 | J Biomol Struct Dyn | Other Topics | 0.000003 | 80.368 | 0.000006 | 194 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2007.05494 | null | Yes | null | null | 2,020 | 2020-07-01 | Preprint | arXiv | 0 | automatic detection of covid-19 cases on x-ray images using convolutional neural networks | In recent months the world has been surprised by the rapid advance of COVID-19. In order to face this disease and minimize its socio-economic impacts, in addition to surveillance and treatment, diagnosis is a crucial procedure. However, the realization of this is hampered by the delay and the limited access to laborato... | 182 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2004.03698 | null | Yes | null | null | 2,020 | 2020-04-07 | Preprint | arXiv | 0 | coronavirus (covid-19) classification using deep features fusion and ranking technique | Coronavirus (COVID-19) emerged towards the end of 2019. World Health Organization (WHO) was identified it as a global epidemic. Consensus occurred in the opinion that using Computerized Tomography (CT) techniques for early diagnosis of pandemic disease gives both fast and accurate results. It was stated by expert radio... | 185 | COVID-19 | null | null | Transfer Learning;World Health Organization;Tomography | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
32968435 | 10.3892/etm.2020.9210 | Yes | PMC7500043 | 32,968,435 | 2,020 | 2020-09-25 | Journal Article | Peer reviewed (PubMed) | 1 | advancing covid-19 differentiation with a robust preprocessing and integration of multi-institutional open-repository computer tomography datasets for deep learning analysis | The coronavirus pandemic and its unprecedented consequences globally has spurred the interest of the artificial intelligence research community. A plethora of published studies have investigated the role of imaging such as chest X-rays and computer tomography in coronavirus disease 2019 (COVID-19) automated diagnosis. ... | 186 | COVID-19;Pneumonia | 4 | Exp Ther Med | Art;Transfer Learning;Tomography;Area under Curve | 0.000001 | 2.4 | 0.000001 | 8 | 0 | External | 2. Detection/Diagnosis | CT |
32834641 | 10.1016/j.chaos.2020.110153 | Yes | PMC7381895 | 32,834,641 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | automatic distinction between covid-19 and common pneumonia using multi-scale convolutional neural network on chest ct scans | The COVID-19 pneumonia is a global threat since it emerged in early December 2019. Driven by the desire to develop a computer-aided system for the rapid diagnosis of COVID-19 to assist radiologists and clinicians to combat with this pandemic, we retrospectively collected 206 patients with positive reverse-transcription... | 186 | COVID-19;Pneumonia | 43 | Chaos Solitons Fractals | Polymerase Chain Reaction;Reverse Transcription | 0.000003 | 50.008 | 0.000003 | 139 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
34127870 | 10.1016/j.patcog.2021.108109 | Yes | PMC8189738 | 34,127,870 | 2,021 | 2021-06-16 | Journal Article | Peer reviewed (PubMed) | 1 | scoat-net: a novel network for segmenting covid-19 lung opacification from ct images | Automatic segmentation of lung opacification from computed tomography (CT) images shows excellent potential for quickly and accurately quantifying the infection of Coronavirus disease 2019 (COVID-19) and judging the disease development and treatment response. However, some challenges still exist, including the complexi... | 187 | COVID-19;Infections | 12 | Pattern Recognit | Art;Noise;Attention;Tomography;Lung Diseases | 0.000002 | 23.88 | 0.000002 | 49 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
34764548 | 10.1007/s10489-020-01829-7 | Yes | PMC7474514 | 34,764,548 | 2,020 | 2020-09-05 | Journal Article | Peer reviewed (PubMed) | 1 | classification of covid-19 in chest x-ray images using detrac deep convolutional neural network | Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (CNN s) for image recognition and classification. However, due to the li... | 187 | COVID-19;Severe Acute Respiratory Syndrome | 250 | Appl Intell (Dordr) | Transfer Learning;Other Topics | 0.000005 | 129.232 | 0.000009 | 290 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33037212 | 10.1038/s41467-020-18685-1 | Yes | PMC7547659 | 33,037,212 | 2,020 | 2020-10-11 | Evaluation Study;Journal Article;Multicenter Study;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | development and evaluation of an artificial intelligence system for covid-19 diagnosis | Early detection of COVID-19 based on chest CT enables timely treatment of patients and helps control the spread of the disease. We proposed an artificial intelligence (AI) system for rapid COVID-19 detection and performed extensive statistical analysis of CTs of COVID-19 based on the AI system. We developed and evaluat... | 187 | COVID-19;Influenza, Human;Pneumonia | 174 | Nat Commun | Coronavirus Infections;ROC Curve;Age | 0.000005 | 120.288 | 0.000007 | 312 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | Multimodal |
32836613 | 10.1007/s40009-020-01009-8 | Yes | PMC7391230 | 32,836,613 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | non-invasive technique-based novel corona(covid-19) virus detection using cnn | A novel human coronavirus 2 (SARS-CoV-2) is an extremely acute respiratory syndrome which was reported in Wuhan, China in the later half 2019. Most of its primary epidemiological aspects are not appropriately known, which has a direct effect on monitoring, practices and controls. The main objective of this work is to p... | 187 | COVID-19;Syndrome | 5 | Natl Acad Sci Lett | Other Topics | 0.000002 | 21.192 | 0.000002 | 65 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2011.00631 | null | Yes | null | null | 2,020 | 2020-11-01 | Preprint | arXiv | 0 | bifurcated autoencoder for segmentation of covid-19 infected regions in ct images | The new coronavirus infection has shocked the world since early 2020 with its aggressive outbreak. Rapid detection of the disease saves lives, and relying on medical imaging (Computed Tomography and X-ray) to detect infected lungs has shown to be effective. Deep learning and convolutional neural networks have been used... | 188 | COVID-19;Coronavirus Infections | null | null | Coronavirus Infections;Art;Algorithms;Disease Outbreaks;Tomography;Lung Diseases | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
33571095 | 10.1109/TNNLS.2021.3054306 | Yes | null | 33,571,095 | 2,021 | 2021-02-12 | Journal Article | Peer reviewed (PubMed) | 1 | an uncertainty-aware transfer learning-based framework for covid-19 diagnosis | The early and reliable detection of COVID-19 infected patients is essential to prevent and limit its outbreak. The PCR tests for COVID-19 detection are not available in many countries, and also, there are genuine concerns about their reliability and performance. Motivated by these shortcomings, this article proposes a ... | 189 | COVID-19 | 28 | IEEE Trans Neural Netw Learn Syst | Reproducibility of Results;Transfer Learning;COVID-19 Testing;Neural Networks;Support Vector Machine;Radiography;Algorithms;Disease Outbreaks;Computer Simulation;Sensitivity and Specificity;Polymerase Chain Reaction;Tomography;ROC Curve;Area under Curve;Receiver Operating Characteristic | 0.000002 | 93.08 | 0.000005 | 205 | 0 | External | 2. Detection/Diagnosis | Multimodal |
33285482 | 10.1016/j.media.2020.101913 | Yes | PMC7689310 | 33,285,482 | 2,020 | 2020-12-08 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | covid-al: the diagnosis of covid-19 with deep active learning | The efficient diagnosis of COVID-19 plays a key role in preventing the spread of this disease. The computer-aided diagnosis with deep learning methods can perform automatic detection of COVID-19 using CT scans. However, large scale annotation of CT scans is impossible because of limited time and heavy burden on the hea... | 190 | COVID-19 | 42 | Med Image Anal | Art;Health Care;Tomography;Other Topics;Lung Diseases | 0.000003 | 57.4 | 0.000004 | 143 | 0 | External | 2. Detection/Diagnosis | CT |
32599338 | 10.1016/j.cmpb.2020.105608 | Yes | PMC7831868 | 32,599,338 | 2,020 | 2020-07-01 | Journal Article | Peer reviewed (PubMed) | 1 | explainable deep learning for pulmonary disease and coronavirus covid-19 detection from x-rays | Coronavirus disease (COVID-19) is an infectious disease caused by a new virus never identified before in humans. This virus causes respiratory disease (for instance, flu) with symptoms such as cough, fever and, in severe cases, pneumonia. The test to detect the presence of this virus in humans is performed on sputum or... | 191 | COVID-19;Communicable Diseases;Cough;Fever;Lung Diseases;Pneumonia;Respiratory Tract Diseases | 182 | Comput Methods Programs Biomed | Coronavirus Infections;Transfer Learning;Algorithms;Image Processing;Lung;Neural Networks;Communicable Diseases | 0.000006 | 133.528 | 0.000008 | 339 | 0 | External | 2. Detection/Diagnosis | X-Ray |
34056622 | 10.1007/s42979-021-00690-w | Yes | PMC8144280 | 34,056,622 | 2,021 | 2021-06-01 | Journal Article | Peer reviewed (PubMed) | 1 | automated covid-19 detection from chest x-ray images: a high-resolution network (hrnet) approach | The pandemic, originated by novel coronavirus 2019 (COVID-19), continuing its devastating effect on the health, well-being, and economy of the global population. A critical step to restrain this pandemic is the early detection of COVID-19 in the human body to constraint the exposure and control the spread of the virus.... | 191 | COVID-19 | 7 | SN Comput Sci | Health Care;Sensitivity and Specificity;Polymerase Chain Reaction;Other Topics | 0.000001 | 10.2 | 0.000001 | 25 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33330341 | 10.3389/fpubh.2020.599550 | Yes | PMC7714903 | 33,330,341 | 2,020 | 2020-12-18 | Journal Article | Peer reviewed (PubMed) | 1 | analysis of covid-19 infections on a ct image using deepsense model | In this paper, a data mining model on a hybrid deep learning framework is designed to diagnose the medical conditions of patients infected with the coronavirus disease 2019 (COVID-19) virus. The hybrid deep learning model is designed as a combination of convolutional neural network (CNN) and recurrent neural network (R... | 191 | COVID-19;Infections | 6 | Front Public Health | Sensitivity and Specificity;Neural Networks | 0.000007 | 135.624 | 0.000008 | 353 | 0 | External | 2. Detection/Diagnosis | CT |
32834651 | 10.1016/j.chaos.2020.110170 | Yes | PMC7388764 | 32,834,651 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | diagnosis and detection of infected tissue of covid-19 patients based on lung x-ray image using convolutional neural network approaches | COVID-19 pandemic has challenged the world science. The international community tries to find, apply, or design novel methods for diagnosis and treatment of COVID-19 patients as soon as possible. Currently, a reliable method for the diagnosis of infected patients is a reverse transcription-polymerase chain reaction. Th... | 192 | COVID-19;COVID-19 Pandemic | 83 | Chaos Solitons Fractals | Polymerase Chain Reaction;Reverse Transcription | 0.000005 | 54.992 | 0.000004 | 138 | 0 | External | 2. Detection/Diagnosis | CT |
2004.13122 | null | Yes | null | null | 2,020 | 2020-04-24 | Preprint | arXiv | 0 | development of a machine-learning system to classify lung ct scan images into normal/covid-19 class | Recently, the lung infection due to Coronavirus Disease (COVID-19) affected a large human group worldwide and the assessment of the infection rate in the lung is essential for treatment planning. This research aims to propose a Machine-Learning-System (MLS) to detect the COVID-19 infection using the CT scan Slices (CTS... | 192 | COVID-19;Infections | null | null | Humans;Other Topics;Entropy;Decision Trees;Support Vector Machine | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
33171723 | 10.3390/jpm10040213 | Yes | PMC7711996 | 33,171,723 | 2,020 | 2020-11-12 | Journal Article | Peer reviewed (PubMed) | 1 | evaluation of scalability and degree of fine-tuning of deep convolutional neural networks for covid-19 screening on chest x-ray images using explainable deep-learning algorithm | According to recent studies, patients with COVID-19 have different feature characteristics on chest X-ray (CXR) than those with other lung diseases. This study aimed at evaluating the layer depths and degree of fine-tuning on transfer learning with a deep convolutional neural network (CNN)-based COVID-19 screening in C... | 193 | COVID-19;Lung Diseases;Pneumonia | 19 | J Pers Med | Transfer Learning;Algorithms;Architecture;Lung;Area under Curve | 0.000006 | 112.864 | 0.000008 | 278 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2004.08379 | null | Yes | null | null | 2,021 | 2021-03-05 | Preprint | arXiv | 0 | iteratively pruned deep learning ensembles for covid-19 detection in chest x-rays | We demonstrate use of iteratively pruned deep learning model ensembles for detecting pulmonary manifestation of COVID-19 with chest X-rays. This disease is caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus, also known as the novel Coronavirus (2019-nCoV). A custom convolutional neur... | 193 | COVID-19;Pneumonia, Bacterial;Severe Acute Respiratory Syndrome | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
35054267 | 10.3390/diagnostics12010101 | Yes | PMC8774807 | 35,054,267 | 2,022 | 2022-01-22 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning-based four-region lung segmentation in chest radiography for covid-19 diagnosis | Imaging plays an important role in assessing the severity of COVID-19 pneumonia. Recent COVID-19 research indicates that the disease progress propagates from the bottom of the lungs to the top. However, chest radiography (CXR) cannot directly provide a quantitative metric of radiographic opacities, and existing AI-assi... | 194 | COVID-19;Edema;Pneumonia;Rales | 5 | Diagnostics (Basel) | Other Topics | 0.000001 | 4.2 | 0.000001 | 7 | 0 | External | Segmentation-only | X-Ray |
2011.05186 | null | Yes | null | null | 2,020 | 2020-11-10 | Preprint | arXiv | 0 | pristine annotations-based multi-modal trained artificial intelligence solution to triage chest x-ray for covid-19 | The COVID-19 pandemic continues to spread and impact the well-being of the global population. The front-line modalities including computed tomography (CT) and X-ray play an important role for triaging COVID patients. Considering the limited access of resources (both hardware and trained personnel) and decontamination c... | 194 | COVID-19;COVID-19 Pandemic | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
34770423 | 10.3390/s21217116 | Yes | PMC8587284 | 34,770,423 | 2,021 | 2021-11-14 | Journal Article | Peer reviewed (PubMed) | 1 | impact of lung segmentation on the diagnosis and explanation of covid-19 in chest x-ray images | COVID-19 frequently provokes pneumonia, which can be diagnosed using imaging exams. Chest X-ray (CXR) is often useful because it is cheap, fast, widespread, and uses less radiation. Here, we demonstrate the impact of lung segmentation in COVID-19 identification using CXR images and evaluate which contents of the image ... | 194 | COVID-19;Pneumonia | 32 | Sensors (Basel) | Semantics;Bias;Other Topics;ROC Curve | 0.000002 | 70.4 | 0.000005 | 148 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33560995 | 10.1109/JBHI.2021.3058293 | Yes | PMC8545167 | 33,560,995 | 2,021 | 2021-02-10 | Journal Article | Peer reviewed (PubMed) | 1 | multiscale attention guided network for covid-19 diagnosis using chest x-ray images | Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic capability when handling COVID-19. However, classifying COVID-19 from pneumonia c... | 194 | COVID-19;Infections;Pneumonia | 15 | IEEE J Biomed Health Inform | Radiography;Health;Noise;Attention;Collection;Lung Diseases;Map | 0.000001 | 38.36 | 0.000003 | 81 | 0 | External | 2. Detection/Diagnosis | X-Ray |
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