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10.1101/2020.07.02.20136721 | 10.1101/2020.07.02.20136721 | Yes | null | null | 2,020 | 2020-07-05 | Preprint | medRxiv | 0 | an automatic computer-based method for fast and accurate covid-19 diagnosis | At present, the whole world is witnessing a horrifying outbreak caused by the Coronavirus Disease 2019 (COVID-19). The virus responsible for this disease is called SARS-CoV-2. It affects its victims’ respiratory system and causes severe lung inflammation, making it harder for them to breathe. The virus is airborne, and... | 231 | COVID-19;Infections;Pneumonitis | null | null | Disease Outbreaks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
33169117 | 10.1016/j.ibmed.2020.100013 | Yes | PMC7641591 | 33,169,117 | 2,020 | 2020-11-11 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning and its role in covid-19 medical imaging | COVID-19 is one of the greatest global public health challenges in history. COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is estimated to have an cumulative global case-fatality rate as high as 7.2% (Onder et al., 2020) . As the SARS-CoV-2 spread across the globe it catalyze... | 232 | COVID-19;Severe Acute Respiratory Syndrome;Virus Diseases | 22 | Intell Based Med | Public Health;Health Care;Polymerase Chain Reaction;Other Topics;Pharmaceutical Preparations | 0.000002 | 25.056 | 0.000002 | 82 | 0 | N.A. | Review | Multimodal |
2008.08840 | null | Yes | null | null | 2,021 | 2021-01-18 | Preprint | arXiv | 0 | image quality assessment for closed-loop computer-assisted lung ultrasound | We describe a novel, two-stage computer assistance system for lung anomaly detection using ultrasound imaging in the intensive care setting to improve operator performance and patient stratification during coronavirus pandemics. The proposed system consists of two deep-learning-based models: a quality assessment module... | 234 | COVID-19 | null | null | Point-of-Care Systems;Ultrasonography | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | Ultrasound |
32496988 | 10.2174/1573405616666200604163954 | Yes | null | 32,496,988 | 2,020 | 2020-06-05 | Journal Article | Peer reviewed (PubMed) | 1 | a deep neural network to distinguish covid-19 from other chest diseases using x-ray images | Scanning a patient's lungs to detect Coronavirus 2019 (COVID-19) may lead to similar imaging of other chest diseases. Thus, a multidisciplinary approach is strongly required to confirm the diagnosis. There are only a few works targeted at pathological x-ray images. Most of the works only target single disease detection... | 234 | COVID-19;Pneumonia | 19 | Curr Med Imaging | Art;Health Care;Neural Networks;Other Topics;Lung Diseases | 0.000001 | 19.44 | 0.000001 | 48 | 0 | External | 2. Detection/Diagnosis | X-Ray |
34038371 | 10.1109/TNNLS.2021.3082015 | Yes | null | 34,038,371 | 2,021 | 2021-05-27 | Journal Article | Peer reviewed (PubMed) | 1 | 4s-dt: self-supervised super sample decomposition for transfer learning with application to covid-19 detection | Due to the high availability of large-scale annotated image datasets, knowledge transfer from pretrained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with data irregularity or imbalanced classes can be a very challenging task, ... | 234 | COVID-19 | 14 | IEEE Trans Neural Netw Learn Syst | Reproducibility of Results;Algorithms;Transfer Learning;Neural Networks;Other Topics;ROC Curve | 0.000003 | 58.84 | 0.000004 | 127 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33125051 | 10.1093/jamia/ocaa280 | Yes | PMC7665533 | 33,125,051 | 2,020 | 2020-10-31 | Journal Article | Peer reviewed (PubMed) | 1 | flannel: focal loss based neural network ensemble for covid-19 detection | The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks. We construct the radiography (x-ray) imaging data from 2 publicly available sources, which include 5508 chest x-ray images across... | 234 | COVID-19;Pneumonia;Pneumonia, Bacterial;Pneumonia, Viral | 11 | J Am Med Inform Assoc | Art;Algorithms;Neural Networks;Other Topics;ROC Curve | 0.000004 | 92.432 | 0.000006 | 234 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32864270 | 10.7759/cureus.9448 | Yes | PMC7451075 | 32,864,270 | 2,020 | 2020-08-31 | Journal Article | Peer reviewed (PubMed) | 1 | predicting covid-19 pneumonia severity on chest x-ray with deep learning | The need to streamline patient management for coronavirus disease-19 (COVID-19) has become more pressing than ever. Chest X-rays (CXRs) provide a non-invasive (potentially bedside) tool to monitor the progression of the disease. In this study, we present a severity score prediction model for COVID-19 pneumonia for fron... | 234 | COVID-19;Infections;Pneumonia | 97 | Cureus | Neural Networks;Other Topics | 0.000003 | 54.48 | 0.000004 | 146 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
2009.06412 | null | Yes | null | null | 2,022 | 2022-05-16 | Preprint | arXiv | 0 | comprehensive comparison of deep learning models for lung and covid-19 lesion segmentation in ct scans | Recently there has been an explosion in the use of Deep Learning (DL) methods for medical image segmentation. However the field's reliability is hindered by the lack of a common base of reference for accuracy/performance evaluation and the fact that previous research uses different datasets for evaluation. In this pape... | 235 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | Segmentation-only | CT |
10.1101/2020.08.18.20175521 | 10.1101/2020.08.18.20175521 | Yes | null | null | 2,020 | 2020-08-21 | Preprint | medRxiv | 0 | machine learning and ai aided tool to differentiate covid-19 and non-covid-19 lung cxr | One of the main challenges in dealing with the current COVID 19 pandemic is how to detect and distinguish between the COVID 19 and non COVID 19 cases. This problem arises since COVID 19 symptoms resemble with other cases. One of the golden standards is by examining the lung using the chest X ray radiograph (CXR). Curre... | 235 | COVID-19;COVID-19 Pandemic;Influenza, Human;Tuberculosis | null | null | Health;Eyeglasses | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2005.02167 | null | Yes | null | null | 2,020 | 2020-04-30 | Preprint | arXiv | 0 | intra-model variability in covid-19 classification using chest x-ray images | X-ray and computed tomography (CT) scanning technologies for COVID-19 screening have gained significant traction in AI research since the start of the coronavirus pandemic. Despite these continuous advancements for COVID-19 screening, many concerns remain about model reliability when used in a clinical setting. Much ha... | 235 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2007.04774 | 10.1016/j.imu.2021.100681. | Yes | null | null | 2,020 | 2020-06-24 | Preprint | arXiv | 0 | automated chest ct image segmentation of covid-19 lung infection based on 3d u-net | The coronavirus disease 2019 (COVID-19) affects billions of lives around the world and has a significant impact on public healthcare. Due to rising skepticism towards the sensitivity of RT-PCR as screening method, medical imaging like computed tomography offers great potential as alternative. For this reason, automated... | 235 | COVID-19;Infections | null | null | Art;Health Care;Architecture;Polymerase Chain Reaction;Tomography;Other Topics;Lung Diseases | null | null | null | null | null | External | Segmentation-only | CT |
32773400 | 10.3233/XST-200715 | Yes | PMC7592691 | 32,773,400 | 2,020 | 2020-08-11 | Comparative Study;Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | identification of covid-19 samples from chest x-ray images using deep learning: a comparison of transfer learning approaches | The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. Rapid detection of COVID-19 cases is a significant step to fight against this viru... | 236 | COVID-19;COVID-19 Pandemic;Death;Pneumonia | 94 | J Xray Sci Technol | Coronavirus Infections;Public Health;Health Care;Transfer Learning;Algorithms;Neural Networks;Health Care Systems;Tomography | 0.000012 | 339.36 | 0.00002 | 834 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32843849 | 10.1016/j.procbio.2020.08.016 | Yes | PMC7439988 | 32,843,849 | 2,020 | 2020-08-28 | Journal Article;Review | Peer reviewed (PubMed) | 1 | a systematic review on recent trends in transmission diagnosis prevention and imaging features of covid-19 | As the new cases of COVID-19 are growing every daysince January 2020, the major way to control the spread wasthrough early diagnosis. Prevention and early diagnosis are the key strategies followed by most countries. This study presents the perspective of different modes of transmission of coronavirus,especially during ... | 237 | COVID-19;Infections | 47 | Process Biochem | Coronavirus Infections;Systematic Review;Polymerase Chain Reaction;Tomography;Reverse Transcription | 0.000002 | 20.112 | 0.000001 | 56 | 0 | N.A. | Review | Multimodal |
32958781 | 10.1038/s41598-020-71294-2 | Yes | PMC7506559 | 32,958,781 | 2,020 | 2020-09-23 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19 image classification using deep features and fractional-order marine predators algorithm | Currently, we witness the severe spread of the pandemic of the new Corona virus, COVID-19, which causes dangerous symptoms to humans and animals, its complications may lead to death. Although convolutional neural networks (CNNs) is considered the current state-of-the-art image classification technique, it needs massive... | 237 | COVID-19;Calculi;Death | 75 | Sci Rep | Coronavirus Infections;Art;Algorithms;Architecture;Research Personnel;Image Processing;Neural Networks | 0.000006 | 105.448 | 0.000007 | 269 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2009.10141 | 10.1007/s42600-020-00110-7 | Yes | null | null | 2,020 | 2020-09-21 | Preprint | arXiv | 0 | ccblock: an effective use of deep learning for automatic diagnosis of covid-19 using x-ray images | Troubling countries one after another, the COVID-19 pandemic has dramatically affected the health and well-being of the world's population. The disease may continue to persist more extensively due to the increasing number of new cases daily, the rapid spread of the virus, and delay in the PCR analysis results. Therefor... | 237 | COVID-19;COVID-19 Pandemic;Pneumonia | null | null | Polymerase Chain Reaction;Other Topics | 0.000001 | 0 | 0 | 0 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33144676 | 10.1038/s41598-020-76141-y | Yes | PMC7641115 | 33,144,676 | 2,020 | 2020-11-05 | Journal Article | Peer reviewed (PubMed) | 1 | the study of automatic machine learning base on radiomics of non-focus area in the first chest ct of different clinical types of covid-19 pneumonia | To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-ML). 136 moderate and 83 severe patients were selected from the patien... | 237 | COVID-19;Pneumonia;Virus Diseases | 14 | Sci Rep | Coronavirus Infections;ROC Curve;Lung Diseases;Age | 0.000003 | 46.488 | 0.000002 | 147 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32524445 | 10.1007/s13246-020-00865-4 | Yes | PMC7118364 | 32,524,445 | 2,020 | 2020-06-12 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19: automatic detection from x-ray images utilizing transfer learning with convolutional neural networks | In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection of the Coronavirus disease. The aim of the study is to evaluate the performance of state-of-the-art convolutional neural network architecture... | 238 | COVID-19;Pneumonia, Bacterial;Pneumonia, Viral | 680 | Phys Eng Sci Med | Radiography;Coronavirus Infections;Art;Transfer Learning;Diagnostic Tests;Architecture;COVID-19 Testing;Sensitivity and Specificity;Neural Networks | 0.000015 | 330.224 | 0.000021 | 812 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32758014 | 10.1259/bjr.20200538 | Yes | PMC7465853 | 32,758,014 | 2,020 | 2020-08-08 | Journal Article;Review | Peer reviewed (PubMed) | 1 | imaging of covid-19 pneumonia: patterns pathogenesis and advances | COVID-19 pneumonia is a newly recognized lung infection. Initially, CT imaging was demonstrated to be one of the most sensitive tests for the detection of infection. Currently, with broader availability of polymerase chain reaction for disease diagnosis, CT is mainly used for the identification of complications and oth... | 238 | COVID-19;Infections;Lung Diseases;Pneumonia | 20 | Br J Radiol | Coronavirus Infections;Polymerase Chain Reaction | 0.000002 | 25.704 | 0.000001 | 97 | 0 | N.A. | Review | Multimodal |
33166256 | 10.1109/JBHI.2020.3036722 | Yes | null | 33,166,256 | 2,020 | 2020-11-10 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | classification of severe and critical covid-19 using deep learning and radiomics | The coronavirus disease 2019 (COVID-19) is rapidly spreading inside China and internationally. We aimed to construct a model integrating information from radiomics and deep learning (DL) features to discriminate critical cases from severe cases of COVID-19 using computed tomography (CT) images. We retrospectively enrol... | 238 | COVID-19;Chronic Disease | 28 | IEEE J Biomed Health Inform | Other Topics | 0.000002 | 21.336 | 0.000002 | 69 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
32868956 | 10.1016/j.patcog.2020.107613 | Yes | PMC7448783 | 32,868,956 | 2,020 | 2020-09-02 | Journal Article | Peer reviewed (PubMed) | 1 | automatically discriminating and localizing covid-19 from community-acquired pneumonia on chest x-rays | The COVID-19 outbreak continues to threaten the health and life of people worldwide. It is an immediate priority to develop and test a computer-aided detection (CAD) scheme based on deep learning (DL) to automatically localize and differentiate COVID-19 from community-acquired pneumonia (CAP) on chest X-rays. Therefore... | 238 | COVID-19;Pneumonia | 67 | Pattern Recognit | Disease Outbreaks;Radiologists | 0.000002 | 43.152 | 0.000003 | 104 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33718884 | 10.1007/s42979-021-00496-w | Yes | PMC7944725 | 33,718,884 | 2,021 | 2021-03-16 | Journal Article | Peer reviewed (PubMed) | 1 | identification of images of covid-19 from chest x-rays using deep learning: comparing cognex visionpro deep learning 10 software with open source convolutional neural networks | The novel Coronavirus, COVID-19, pandemic is being considered the most crucial health calamity of the century. Many organizations have come together during this crisis and created various Deep Learning models for the effective diagnosis of COVID-19 from chest radiography images. For example, The University of Waterloo,... | 238 | COVID-19;COVID-19 Pandemic | 11 | SN Comput Sci | Black Americans;Art;Health;X-Rays;Dataset;Other Topics | 0.000001 | 30.36 | 0.000002 | 69 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32666395 | 10.1007/s00259-020-04953-1 | Yes | PMC7358997 | 32,666,395 | 2,020 | 2020-07-16 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | automated detection and quantification of covid-19 pneumonia: ct imaging analysis by a deep learning-based software | The novel coronavirus disease 2019 (COVID-19) is an emerging worldwide threat to public health. While chest computed tomography (CT) plays an indispensable role in its diagnosis, the quantification and localization of lesions cannot be accurately assessed manually. We employed deep learning-based software to aid in det... | 239 | COVID-19;Infections;Pneumonia | 49 | Eur J Nucl Med Mol Imaging | Coronavirus Infections;Public Health;COVID-19 Testing;Polymerase Chain Reaction;Retrospective Studies | 0.000005 | 122.192 | 0.000006 | 358 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
34786299 | 10.1109/ACCESS.2020.3044858 | Yes | PMC8545248 | 34,786,299 | 2,021 | 2021-11-18 | Journal Article | Peer reviewed (PubMed) | 1 | artificial intelligence applied to chest x-ray images for the automatic detection of covid-19 a thoughtful evaluation approach | Current standard protocols used in the clinic for diagnosing COVID-19 include molecular or antigen tests, generally complemented by a plain chest X-Ray. The combined analysis aims to reduce the significant number of false negatives of these tests and provide complementary evidence about the presence and severity of the... | 239 | COVID-19;Pneumonia | 26 | IEEE Access | Other Topics | 0.000002 | 29.512 | 0.000003 | 79 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32982615 | 10.1016/j.asoc.2020.106742 | Yes | PMC7505822 | 32,982,615 | 2,020 | 2020-09-29 | Journal Article | Peer reviewed (PubMed) | 1 | an optimized deep learning architecture for the diagnosis of covid-19 disease based on gravitational search optimization | In this paper, a novel approach called GSA-DenseNet121-COVID-19 based on a hybrid convolutional neural network (CNN) architecture is proposed using an optimization algorithm. The CNN architecture that was used is called DenseNet121, and the optimization algorithm that was used is called the gravitational search algorit... | 239 | COVID-19 | 51 | Appl Soft Comput | Algorithms;Transfer Learning;Architecture | 0.000003 | 37.504 | 0.000003 | 98 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2006.13262 | null | Yes | null | null | 2,020 | 2020-06-23 | Preprint | arXiv | 0 | was there covid-19 back in 2012? challenge for ai in diagnosis with similar indications | Since the recent COVID-19 outbreak, there has been an avalanche of research papers applying deep learning based image processing to chest radiographs for detection of the disease. To test the performance of the two top models for CXR COVID-19 diagnosis on external datasets to assess model generalizability. In this pape... | 240 | COVID-19;Infections | null | null | Disease Outbreaks;Polymerase Chain Reaction;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32555006 | 10.1097/RTI.0000000000000544 | Yes | PMC7682797 | 32,555,006 | 2,020 | 2020-06-20 | Journal Article | Peer reviewed (PubMed) | 1 | a novel machine learning-derived radiomic signature of the whole lung differentiates stable from progressive covid-19 infection: a retrospective cohort study | This study aimed to use the radiomics signatures of a machine learning-based tool to evaluate the prognosis of patients with coronavirus disease 2019 (COVID-19) infection. The clinical and imaging data of 64 patients with confirmed diagnoses of COVID-19 were retrospectively selected and divided into a stable group and ... | 240 | COVID-19;Cough;Infections | 25 | J Thorac Imaging | Severity of Illness Index;Sensitivity;C-Reactive Protein;Humans;Retrospective Studies;Entropy;Support Vector Machine;Area under Curve;Age | 0.000002 | 36.312 | 0.000002 | 103 | 0 | External | 4. Prognosis/Treatment | CT |
34108787 | 10.1016/j.bbe.2021.05.013 | Yes | PMC8179118 | 34,108,787 | 2,021 | 2021-06-11 | Journal Article | Peer reviewed (PubMed) | 1 | automatic detection of coronavirus disease (covid-19) in x-ray and ct images: a machine learning-based approach | The newly identified Coronavirus pneumonia, subsequently termed COVID-19, is highly transmittable and pathogenic with no clinically approved antiviral drug or vaccine available for treatment. The most common symptoms of COVID-19 are dry cough, sore throat, and fever. Symptoms can progress to a severe form of pneumonia ... | 241 | COVID-19;Cough;Fever;Pneumonia;Pulmonary Edema;Respiratory Distress Syndrome, Acute;Shock, Septic;Sore Throat | 86 | Biocybern Biomed Eng | Transfer Learning;Lung;Antiviral Agents;Pharmaceutical Preparations | 0.000003 | 91.48 | 0.000006 | 191 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33025386 | 10.1007/s13246-020-00934-8 | Yes | PMC7537970 | 33,025,386 | 2,020 | 2020-10-08 | Journal Article | Peer reviewed (PubMed) | 1 | issues associated with deploying cnn transfer learning to detect covid-19 from chest x-rays | Covid-19 first occurred in Wuhan, China in December 2019. Subsequently, the virus spread throughout the world and as of June 2020 the total number of confirmed cases are above 4.7 million with over 315,000 deaths. Machine learning algorithms built on radiography images can be used as a decision support mechanism to aid... | 241 | COVID-19;Death | 21 | Phys Eng Sci Med | Algorithms;Transfer Learning;Architecture;Image Processing;Neural Networks;Map | 0.000004 | 140.592 | 0.00001 | 300 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33230395 | 10.1016/j.asoc.2020.106912 | Yes | PMC7673219 | 33,230,395 | 2,020 | 2020-11-25 | Journal Article | Peer reviewed (PubMed) | 1 | cnn-based transfer learning-bilstm network: a novel approach for covid-19 infection detection | Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019 and has spread rapidly all over the world since the beginning of 2020, has infected millions of people and caused many deaths. For this pandemic, which is still in effect, mobilization has started all over the world, and various restrictions a... | 241 | COVID-19;Death;Infections | 98 | Appl Soft Comput | Transfer Learning;Architecture;Lung;Polymerase Chain Reaction;Tomography;Reverse Transcription | 0.000004 | 66.608 | 0.000005 | 170 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2008.06330 | null | Yes | null | null | 2,020 | 2020-08-13 | Preprint | arXiv | 0 | automated detection and quantification of covid-19 airspace disease on chest radiographs: a novel approach achieving radiologist-level performance using a cnn trained on digital reconstructed radiographs (drrs) from ct-based ground-truth | To leverage volumetric quantification of airspace disease (AD) derived from a superior modality (CT) serving as ground truth, projected onto digitally reconstructed radiographs (DRRs) to: 1) train a convolutional neural network to quantify airspace disease on paired CXRs; and 2) compare the DRR-trained CNN to expert hu... | 241 | COVID-19 | null | null | Polymerase Chain Reaction;Other Topics | null | null | null | null | null | Self-recorded/clinical | 3. Monitoring/Severity assessment | Multimodal |
10.1101/2020.09.07.20189852 | 10.1101/2020.09.07.20189852 | Yes | null | null | 2,020 | 2020-09-09 | Preprint | medRxiv | 0 | network for subclinical prognostication of covid-19 patients from data of thoracic roentgenogram: a feasible alternative screening technology | COVID 19 is the terminology driving people’s life in the year 2020 without a supportive globally high mortality rate. Coronavirus lead pandemic is a new found disease with no gold standard diagnostic and therapeutic guideline across the globe. Amidst this scenario our aim is to develop a prediction model that makes mas... | 241 | COVID-19;Strains | null | null | Health Care;Sensitivity and Specificity;Polymerase Chain Reaction;Area under Curve | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.08.12.20173872 | 10.1101/2020.08.12.20173872 | Yes | null | null | 2,020 | 2020-08-14 | Preprint | medRxiv | 0 | severity assessment of covid-19 based on clinical and imaging data | This study aims to develop a machine learning approach for automated severity assessment of COVID-19 patients based on clinical and imaging data. Clinical data, demographics, signs, symptoms, comorbidities and blood test results, and chest CT scans of 346 patients from two hospitals in the Hubei province, China, were u... | 241 | COVID-19 | null | null | COVID-19 Testing;Hematologic Tests | null | null | null | null | null | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
2009.10401 | null | Yes | null | null | 2,020 | 2020-10-25 | Preprint | arXiv | 0 | dynamic fusion based federated learning for covid-19 detection | Medical diagnostic image analysis (e.g., CT scan or X-Ray) using machine learning is an efficient and accurate way to detect COVID-19 infections. However, sharing diagnostic images across medical institutions is usually not allowed due to the concern of patients' privacy. This causes the issue of insufficient datasets ... | 241 | COVID-19;Infections | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
33180877 | 10.1371/journal.pone.0242301 | Yes | PMC7660555 | 33,180,877 | 2,020 | 2020-11-13 | Journal Article;Research Support, N.I.H., Intramural | Peer reviewed (PubMed) | 1 | analyzing inter-reader variability affecting deep ensemble learning for covid-19 detection in chest radiographs | Data-driven deep learning (DL) methods using convolutional neural networks (CNNs) demonstrate promising performance in natural image computer vision tasks. However, their use in medical computer vision tasks faces several limitations, viz., adapting to visual characteristics that are unlike natural images; modeling ran... | 241 | COVID-19 | 26 | PLoS One | Radiography;Coronavirus Infections;Black Americans;Noise;X-Rays;Image Processing;Neural Networks | 0.000005 | 78.568 | 0.000005 | 231 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2011.11736 | null | Yes | null | null | 2,021 | 2021-01-08 | Preprint | arXiv | 0 | accurate and rapid diagnosis of covid-19 pneumonia with batch effect removal of chest ct-scans and interpretable artificial intelligence | COVID-19 is a virus with high transmission rate that demands rapid identification of the infected patients to reduce the spread of the disease. The current gold-standard test, Reverse-Transcription Polymerase Chain Reaction (RT-PCR), has a high rate of false negatives. Diagnosing from CT-scan images as a more accurate ... | 242 | COVID-19;Pneumonia | null | null | Polymerase Chain Reaction;Reverse Transcription | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
2012.14106 | null | Yes | null | null | 2,020 | 2020-12-28 | Preprint | arXiv | 0 | diagnosis/prognosis of covid-19 images: challenges opportunities and applications | The novel Coronavirus disease, COVID-19, has rapidly and abruptly changed the world as we knew in 2020. It becomes the most unprecedent challenge to analytic epidemiology in general and signal processing theories in specific. Given its high contingency nature and adverse effects across the world, it is important to dev... | 242 | COVID-19;Infections | null | null | Other Topics | null | null | null | null | null | N.A. | Review | Multimodal |
32921934 | 10.1016/j.chaos.2020.110245 | Yes | PMC7472981 | 32,921,934 | 2,020 | 2020-09-15 | Journal Article | Peer reviewed (PubMed) | 1 | cvdnet: a novel deep learning architecture for detection of coronavirus (covid-19) from chest x-ray images | The COVID-19 pandemic is an emerging respiratory infectious disease, also known as coronavirus 2019. It appears in November 2019 in Hubei province (in China), and more specifically in the city of Wuhan, then spreads in the whole world. As the number of cases increases with unprecedented speed, many parts of the world a... | 243 | COVID-19;COVID-19 Pandemic;Communicable Diseases;Infections;Pneumonia;Pneumonia, Viral | 73 | Chaos Solitons Fractals | Coronavirus Infections;Health Care;Communicable Diseases | 0.000008 | 171.512 | 0.000011 | 433 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32350794 | 10.1007/s11547-020-01197-9 | Yes | PMC7189175 | 32,350,794 | 2,020 | 2020-05-01 | Journal Article | Peer reviewed (PubMed) | 1 | use of ct and artificial intelligence in suspected or covid-19 positive patients: statement of the italian society of medical and interventional radiology | The COVID-19 pandemic started in Italy in February 2020 with an exponential growth that has exceeded the number of cases reported in China. Italian radiology departments found themselves at the forefront in the management of suspected and positive COVID cases, both in diagnosis, in estimating the severity of the diseas... | 243 | COVID-19;COVID-19 Pandemic;Coronavirus Infections;Pneumonia | 78 | Radiol Med | Coronavirus Infections;Polymerase Chain Reaction | 0.000006 | 96.576 | 0.000005 | 294 | 0 | N.A. | Review | CT |
33134214 | 10.31661/jbpe.v0i0.2008-1153 | Yes | PMC7557468 | 33,134,214 | 2,020 | 2020-11-03 | Journal Article | Peer reviewed (PubMed) | 1 | transfer learning-based automatic detection of coronavirus disease 2019 (covid-19) from chest x-ray images | Coronavirus disease 2019 (COVID-19) is an emerging infectious disease and global health crisis. Although real-time reverse transcription polymerase chain reaction (RT-PCR) is known as the most widely laboratory method to detect the COVID-19 from respiratory specimens. It suffers from several main drawbacks such as time... | 243 | COVID-19;Communicable Diseases, Emerging;Infections | 23 | J Biomed Phys Eng | Transfer Learning;Polymerase Chain Reaction;Retrospective Studies;Area under Curve;Communicable Diseases;Reverse Transcription;Receiver Operating Characteristic | 0.000003 | 66.984 | 0.000005 | 153 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2012.01473 | null | Yes | null | null | 2,020 | 2020-12-02 | Preprint | arXiv | 0 | covsegnet: a multi encoder-decoder architecture for improved lesion segmentation of covid-19 chest ct scans | Automatic lung lesions segmentation of chest CT scans is considered a pivotal stage towards accurate diagnosis and severity measurement of COVID-19. Traditional U-shaped encoder-decoder architecture and its variants suffer from diminutions of contextual information in pooling/upsampling operations with increased semant... | 244 | COVID-19 | null | null | Art;Architecture;Semantics;Tomography;Map;Cone-Beam Computed Tomography | null | null | null | null | null | Self-recorded/clinical | Segmentation-only | CT |
33928256 | 10.1148/ryai.2020200079 | Yes | PMC7392327 | 33,928,256 | 2,021 | 2021-05-01 | Journal Article | Peer reviewed (PubMed) | 1 | automated assessment and tracking of covid-19 pulmonary disease severity on chest radiographs using convolutional siamese neural networks | To develop an automated measure of COVID-19 pulmonary disease severity on chest radiographs (CXRs), for longitudinal disease tracking and outcome prediction. A convolutional Siamese neural network-based algorithm was trained to output a measure of pulmonary disease severity on CXRs (pulmonary x-ray severity (PXS) score... | 244 | COVID-19;Death;Lung Diseases | 67 | Radiol Artif Intell | Transfer Learning;Algorithms;Lung;Receiver Operating Characteristic | 0.000003 | 35.88 | 0.000003 | 91 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | X-Ray |
2005.00845 | null | Yes | null | null | 2,020 | 2020-05-02 | Preprint | arXiv | 0 | deep convolutional neural networks to diagnose covid-19 and other pneumonia diseases from posteroanterior chest x-rays | The article explores different deep convolutional neural network architectures trained and tested on posteroanterior chest X-rays of 327 patients who are healthy (152 patients), diagnosed with COVID-19 , and other types of pneumonia . In particular, this paper looks at the deep convolutional neural networks VGG16 and V... | 244 | COVID-19;Infections;Pneumonia | null | null | Health Care;Polymerase Chain Reaction;Neural Networks;Other Topics;Paper | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33446781 | 10.1038/s41598-020-80936-4 | Yes | PMC7809065 | 33,446,781 | 2,021 | 2021-01-16 | Journal Article;Research Support, N.I.H., Extramural;Research Support, Non-U.S. Gov't;Research Support, U.S. Gov't, Non-P.H.S. | Peer reviewed (PubMed) | 1 | ct image segmentation for inflamed and fibrotic lungs using a multi-resolution convolutional neural network | The purpose of this study was to develop a fully-automated segmentation algorithm, robust to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of computed tomography images. A polymorphic training approach is proposed, in which both specifically labeled left and right lungs of huma... | 244 | Acute Lung Injury;COVID-19;Lung Cancer;Pulmonary Disease, Chronic Obstructive | 22 | Sci Rep | Fibrosis;Neural Networks;Other Topics;Chronic Disease;Cluster Analysis | 0.000001 | 20.44 | 0.000002 | 45 | 0 | External | Segmentation-only | CT |
33231160 | 10.2174/1573405616666201123120417 | Yes | PMC8653418 | 33,231,160 | 2,020 | 2020-11-25 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | deep transfer learning for covid-19 prediction: case study for limited data problems | Automatic prediction of COVID-19 using deep convolution neural networks based pre-trained transfer models and Chest X-ray images. This research employs the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of the disease. Using Dee... | 244 | COVID-19 | 6 | Curr Med Imaging | Transfer Learning;Neural Networks;Other Topics | 0.000003 | 109.88 | 0.000007 | 227 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2009.08864 | null | Yes | null | null | 2,020 | 2020-09-15 | Preprint | arXiv | 0 | classification and region analysis of covid-19 infection using lung ct images and deep convolutional neural networks | COVID-19 is a global health problem. Consequently, early detection and analysis of the infection patterns are crucial for controlling infection spread as well as devising a treatment plan. This work proposes a two-stage deep Convolutional Neural Networks (CNNs) based framework for delineation of COVID-19 infected regio... | 245 | COVID-19;Infections | null | null | Health;Semantics | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
33190102 | 10.1016/j.ejrad.2020.109402 | Yes | PMC7641539 | 33,190,102 | 2,020 | 2020-11-16 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning analysis provides accurate covid-19 diagnosis on chest computed tomography | Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and risk stratification of the disease. A novel deep learning derived machine learning (... | 245 | COVID-19 | 22 | Eur J Radiol | Reproducibility of Results;ROC Curve;Lung Diseases;Age | 0.000003 | 59.992 | 0.000003 | 173 | 0 | External | 2. Detection/Diagnosis | CT |
35789224 | 10.1109/JSEN.2021.3076767 | Yes | PMC8791443 | 35,789,224 | 2,021 | 2021-04-30 | Journal Article | Peer reviewed (PubMed) | 1 | blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging | With the increase of COVID-19 cases worldwide, an effective way is required to diagnose COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage and reliability of testing kits, due to the quick spread of the virus, medical practitioners are facing difficulty in identifying the positive ca... | 245 | COVID-19 | 40 | IEEE Sens J | Other Topics | 0.000002 | 32.24 | 0.000003 | 62 | -1 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33094700 | 10.1152/physiolgenomics.00084.2020 | Yes | PMC7774002 | 33,094,700 | 2,020 | 2020-10-24 | Journal Article | Peer reviewed (PubMed) | 1 | implementation of convolutional neural network approach for covid-19 disease detection | In this paper, two novel, powerful, and robust convolutional neural network (CNN) architectures are designed and proposed for two different classification tasks using publicly available data sets. The first architecture is able to decide whether a given chest X-ray image of a patient contains COVID-19 or not with 98.92... | 245 | COVID-19;Pneumonia | 12 | Physiol Genomics | Architecture;Image Processing;Neural Networks | 0.000008 | 175.264 | 0.000012 | 420 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32730215 | 10.1109/TMI.2020.3000314 | Yes | null | 32,730,215 | 2,020 | 2020-07-31 | Journal Article | Peer reviewed (PubMed) | 1 | a noise-robust framework for automatic segmentation of covid-19 pneumonia lesions from ct images | Segmentation of pneumonia lesions from CT scans of COVID-19 patients is important for accurate diagnosis and follow-up. Deep learning has a potential to automate this task but requires a large set of high-quality annotations that are difficult to collect. Learning from noisy training labels that are easier to obtain ha... | 246 | COVID-19;Pneumonia | 129 | IEEE Trans Med Imaging | Coronavirus Infections;Art;Algorithms;Noise;Tomography | 0.000006 | 102.832 | 0.000007 | 264 | 0 | Self-recorded/clinical | Segmentation-only | CT |
33038076 | 10.2196/21604 | Yes | PMC7674140 | 33,038,076 | 2,020 | 2020-10-11 | Journal Article | Peer reviewed (PubMed) | 1 | prediction of covid-19 severity using chest computed tomography and laboratory measurements: evaluation using a machine learning approach | Most of the mortality resulting from COVID-19 has been associated with severe disease. Effective treatment of severe cases remains a challenge due to the lack of early detection of the infection. This study aimed to develop an effective prediction model for COVID-19 severity by combining radiological outcome with clini... | 247 | COVID-19;Clinical Course;Infections | 11 | JMIR Med Inform | Other Topics | 0.000001 | 19.824 | 0.000001 | 52 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | CT |
33275187 | 10.1007/s13246-020-00952-6 | Yes | PMC7715648 | 33,275,187 | 2,020 | 2020-12-05 | Journal Article | Peer reviewed (PubMed) | 1 | stacknet-denvis: a multi-layer perceptron stacked ensembling approach for covid-19 detection using x-ray images | The highly contagious nature of Coronavirus disease 2019 (Covid-19) resulted in a global pandemic. Due to the relatively slow and taxing nature of conventional testing for Covid-19, a faster method needs to be in place. The current researches have suggested that visible irregularities found in the chest X-ray of Covid-... | 247 | COVID-19;Pneumonia, Viral | 12 | Phys Eng Sci Med | Transfer Learning;Algorithms;Architecture;COVID-19 Testing;Sensitivity and Specificity;Image Processing;Lung;Neural Networks;Paper;ROC Curve;Lung Diseases;Research | 0.000003 | 57.184 | 0.000004 | 138 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2005.01577 | null | Yes | null | null | 2,020 | 2020-04-29 | Preprint | arXiv | 0 | covid-da: deep domain adaptation from typical pneumonia to covid-19 | The outbreak of novel coronavirus disease 2019 (COVID-19) has already infected millions of people and is still rapidly spreading all over the globe. Most COVID-19 patients suffer from lung infection, so one important diagnostic method is to screen chest radiography images, e.g., X-Ray or CT images. However, such examin... | 247 | COVID-19;Infections;Pneumonia | null | null | Disease Outbreaks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33132536 | 10.1007/s00521-020-05437-x | Yes | PMC7586204 | 33,132,536 | 2,020 | 2020-11-03 | Journal Article | Peer reviewed (PubMed) | 1 | a deep transfer learning model with classical data augmentation and cgan to detect covid-19 from chest ct radiography digital images | The Coronavirus disease 2019 (COVID-19) is the fastest transmittable virus caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). The detection of COVID-19 using artificial intelligence techniques and especially deep learning will help to detect this virus in early stages which will reflect in increasi... | 247 | COVID-19;Severe Acute Respiratory Syndrome | 88 | Neural Comput Appl | Health Care;Transfer Learning;Sensitivity and Specificity;Health Care Systems | 0.000006 | 99.56 | 0.000007 | 249 | 0 | External | 2. Detection/Diagnosis | CT |
32722697 | 10.1371/journal.pone.0236621 | Yes | PMC7386587 | 32,722,697 | 2,020 | 2020-07-30 | Journal Article | Peer reviewed (PubMed) | 1 | deep transfer learning artificial intelligence accurately stages covid-19 lung disease severity on portable chest radiographs | This study employed deep-learning convolutional neural networks to stage lung disease severity of Coronavirus Disease 2019 (COVID-19) infection on portable chest x-ray (CXR) with radiologist score of disease severity as ground truth. This study consisted of 131 portable CXR from 84 COVID-19 patients (51M 55.1yo; 29F 60... | 248 | COVID-19;Infections;Lung Diseases | 65 | PLoS One | Other Topics | 0.000004 | 83.456 | 0.000005 | 230 | 0 | External | 3. Monitoring/Severity assessment | X-Ray |
10.1101/2020.10.30.20222786 | 10.1101/2020.10.30.20222786 | Yes | null | null | 2,020 | 2020-11-03 | Preprint | medRxiv | 0 | deep learning model for improving the characterization of coronavirus on chest x-ray images using cnn | The novel Coronavirus, also known as Covid19, is a pandemic that has weighed heavily on the socio-economic affairs of the world. Although researches into the production of relevant vaccine are being advanced, there is, however, a need for a computational solution to mediate the process of aiding quick detection of the ... | 248 | COVID-19 | null | null | Polymerase Chain Reaction;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2010.14091 | null | Yes | null | null | 2,020 | 2020-10-27 | Preprint | arXiv | 0 | triple-view convolutional neural networks for covid-19 diagnosis with chest x-ray | The Coronavirus Disease 2019 (COVID-19) is affecting increasingly large number of people worldwide, posing significant stress to the health care systems. Early and accurate diagnosis of COVID-19 is critical in screening of infected patients and breaking the person-to-person transmission. Chest X-ray (CXR) based compute... | 248 | COVID-19 | null | null | Art;Health Care;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33230398 | 10.1016/j.bspc.2020.102365 | Yes | PMC7674150 | 33,230,398 | 2,020 | 2020-11-25 | Journal Article | Peer reviewed (PubMed) | 1 | application of deep learning techniques for detection of covid-19 cases using chest x-ray images: a comprehensive study | The emergence of Coronavirus Disease 2019 (COVID-19) in early December 2019 has caused immense damage to health and global well-being. Currently, there are approximately five million confirmed cases and the novel virus is still spreading rapidly all over the world. Many hospitals across the globe are not yet equipped w... | 249 | COVID-19;Infections | 106 | Biomed Signal Process Control | Research Personnel;Polymerase Chain Reaction;Reverse Transcription | 0.000007 | 142.696 | 0.00001 | 349 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32729263 | 10.3348/kjr.2020.0536 | Yes | PMC7458860 | 32,729,263 | 2,020 | 2020-07-31 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | implementation of a deep learning-based computer-aided detection system for the interpretation of chest radiographs in patients suspected for covid-19 | To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate the diagnostic performance of CXR interpretation with CAD assistance. In this single-center ... | 249 | COVID-19;Pneumonia | 33 | Korean J Radiol | Coronavirus Infections;COVID-19 Testing;Polymerase Chain Reaction;Retrospective Studies | 0.000007 | 145.064 | 0.000008 | 423 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | Multimodal |
2009.12597 | null | Yes | null | null | 2,021 | 2021-01-21 | Preprint | arXiv | 0 | potential features of icu admission in x-ray images of covid-19 patients | X-ray images may present non-trivial features with predictive information of patients that develop severe symptoms of COVID-19. If true, this hypothesis may have practical value in allocating resources to particular patients while using a relatively inexpensive imaging technique. The difficulty of testing such a hypoth... | 249 | COVID-19 | null | null | Art;Semantics;Other Topics | null | null | null | null | null | External | 4. Prognosis/Treatment | X-Ray |
34764554 | 10.1007/s10489-020-01900-3 | Yes | PMC7568031 | 34,764,554 | 2,021 | 2021-11-13 | Journal Article | Peer reviewed (PubMed) | 1 | automated diagnosis of covid-19 with limited posteroanterior chest x-ray images using fine-tuned deep neural networks | The novel coronavirus 2019 (COVID-19) is a respiratory syndrome that resembles pneumonia. The current diagnostic procedure of COVID-19 follows reverse-transcriptase polymerase chain reaction (RT-PCR) based approach which however is less sensitive to identify the virus at the initial stage. Hence, a more robust and alte... | 249 | COVID-19;Infections;Pneumonia;Syndrome | 55 | Appl Intell (Dordr) | Art;Health Care;Transfer Learning;Research Personnel;Architecture;Polymerase Chain Reaction;Tomography;Area under Curve | 0.000003 | 89.336 | 0.000007 | 199 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.05.24.20111922 | 10.1101/2020.05.24.20111922 | Yes | null | null | 2,020 | 2020-05-25 | Preprint | medRxiv | 0 | aidcov: an interpretable artificial intelligence model for detection of covid-19 from chest radiography images | As the Coronavirus Disease 2019 (COVID-19) pandemic continues to grow globally, testing to detect COVID-19 and isolating individuals who test positive remains to be the primary strategy for preventing community spread of the disease. The current gold standard method of testing for COVID-19 is the reverse transcription ... | 249 | COVID-19;COVID-19 Pandemic;Infections;Pneumonia | null | null | Predictive Value;Sensitivity and Specificity;Polymerase Chain Reaction;Neural Networks;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32836918 | 10.1016/j.chaos.2020.110190 | Yes | PMC7413068 | 32,836,918 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | a deep learning and grad-cam based color visualization approach for fast detection of covid-19 cases using chest x-ray and ct-scan images | The world is suffering from an existential global health crisis known as the COVID-19 pandemic. Countries like India, Bangladesh, and other developing countries are still having a slow pace in the detection of COVID-19 cases. Therefore, there is an urgent need for fast detection with clear visualization of infection is... | 249 | COVID-19;COVID-19 Pandemic;Infections;Pneumonia | 123 | Chaos Solitons Fractals | Algorithms;Transfer Learning;Color;Polymerase Chain Reaction | 0.000006 | 131.808 | 0.000008 | 322 | 0 | External | 2. Detection/Diagnosis | Multimodal |
10.1101/2020.05.12.20098954 | 10.1101/2020.05.12.20098954 | Yes | null | null | 2,020 | 2020-05-19 | Preprint | medRxiv | 0 | covid-19 detection using cnn transfer learning from x-ray images | The Covid-19 first occurs in Wuhan, China in December 2019. After that the virus spread all around the world and at the time of writing this paper the total number of confirmed cases are above 4.7 million with over 315000 deaths. Machine learning algorithms built on radiography images can be used as decision support me... | 249 | Bacterial Infections;COVID-19;Death;Virus Diseases | null | null | Algorithms;Transfer Learning;Architecture;Map | null | null | null | null | null | External | Segmentation-only | X-Ray |
2004.10987 | null | Yes | null | null | 2,020 | 2020-04-25 | Preprint | arXiv | 0 | covid-19 chest ct image segmentation -- a deep convolutional neural network solution | A novel coronavirus disease 2019 (COVID-19) was detected and has spread rapidly across various countries around the world since the end of the year 2019, Computed Tomography (CT) images have been used as a crucial alternative to the time-consuming RT-PCR test. However, pure manual segmentation of CT images faces a seri... | 249 | COVID-19;Infections | null | null | Polymerase Chain Reaction;Other Topics | null | null | null | null | null | Self-recorded/clinical | Segmentation-only | CT |
32834627 | 10.1016/j.chaos.2020.110071 | Yes | PMC7332960 | 32,834,627 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | recognition of covid-19 disease from x-ray images by hybrid model consisting of 2d curvelet transform chaotic salp swarm algorithm and deep learning technique | The novel coronavirus disease 2019 (COVID-19), detected in Wuhan City, Hubei Province, China in late December 2019, is rapidly spreading and affecting all countries in the world. Real-time reverse transcription-polymerase chain reaction (RT-PCR) test has been described by the World Health Organization (WHO) as the stan... | 249 | COVID-19;Pneumonia | 84 | Chaos Solitons Fractals | Occupational Groups;Health Care;World Health Organization;Polymerase Chain Reaction;Reverse Transcription | 0.000004 | 50.352 | 0.000004 | 144 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32927416 | 10.1016/j.ejrad.2020.109233 | Yes | PMC7455238 | 32,927,416 | 2,020 | 2020-09-15 | Journal Article | Peer reviewed (PubMed) | 1 | development and clinical implementation of tailored image analysis tools for covid-19 in the midst of the pandemic: the synergetic effect of an open clinically embedded software development platform and machine learning | During the emerging COVID-19 pandemic, radiology departments faced a substantial increase in chest CT admissions coupled with the novel demand for quantification of pulmonary opacities. This article describes how our clinic implemented an automated software solution for this purpose into an established software platfor... | 250 | COVID-19;COVID-19 Pandemic | 12 | Eur J Radiol | Coronavirus Infections;Neural Networks | 0.000004 | 31.92 | 0.000003 | 120 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
10.1101/2020.12.19.20248530 | 10.1101/2020.12.19.20248530 | Yes | null | null | 2,020 | 2020-12-23 | Preprint | medRxiv | 0 | lungai: a deep learning convolutional neural network for automated detection of covid-19 from posteroanterior chest x-rays | COVID-19 is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). As of December 2020, more than 72 million cases have been reported worldwide. The standard method of diagnosis is by Real-Time Reverse Transcription Polymerase Chain Reaction (rRT-PCR) from a Nasopharyngeal Swa... | 250 | COVID-19;Communicable Diseases;Pneumonia, Bacterial;Pneumonia, Viral;Severe Acute Respiratory Syndrome | null | null | Polymerase Chain Reaction;Antiviral Agents;Pharmaceutical Preparations;Communicable Diseases;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32568676 | 10.1016/j.compbiomed.2020.103795 | Yes | PMC7190523 | 32,568,676 | 2,020 | 2020-06-23 | Journal Article | Peer reviewed (PubMed) | 1 | application of deep learning technique to manage covid-19 in routine clinical practice using ct images: results of 10 convolutional neural networks | Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in high workload conditions. Although a laboratory test is the current routine diagnostic tool, it is time-consuming, imposing a high cost and requirin... | 250 | COVID-19;Infections;Pneumonia, Viral | 291 | Comput Biol Med | Coronavirus Infections;Sensitivity and Specificity;Neural Networks;Area under Curve | 0.000012 | 302.04 | 0.000017 | 791 | 0 | External | 2. Detection/Diagnosis | CT |
33230503 | 10.1016/j.ibmed.2020.100014 | Yes | PMC7674009 | 33,230,503 | 2,020 | 2020-11-25 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19 pneumonia accurately detected on chest radiographs with artificial intelligence | To investigate the diagnostic performance of an Artificial Intelligence (AI) system for detection of COVID-19 in chest radiographs (CXR), and compare results to those of physicians working alone, or with AI support. An AI system was fine-tuned to discriminate confirmed COVID-19 pneumonia, from other viral and bacterial... | 250 | COVID-19;Pneumonia;Pneumonia, Bacterial | 11 | Intell Based Med | Polymerase Chain Reaction;Real-Time Polymerase Chain Reaction | 0.000003 | 46.04 | 0.000003 | 113 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
33209367 | 10.21037/jtd-20-1584 | Yes | PMC7656439 | 33,209,367 | 2,020 | 2020-11-20 | Journal Article | Peer reviewed (PubMed) | 1 | ct imaging features of different clinical types of covid-19 calculated by ai system: a chinese multicenter study | The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system. A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients... | 251 | COVID-19;Fibrosis;Pneumonia | 3 | J Thorac Dis | Dataset;Fibrosis;Radiologists | 0.000002 | 29.304 | 0.000002 | 103 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
2003.13145 | 10.1109/ACCESS.2020.3010287 | Yes | null | null | 2,020 | 2020-06-15 | Preprint | arXiv | 0 | can ai help in screening viral and covid-19 pneumonia? | Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection with high accuracy can be crucially helpful to healthcare professionals. The main clinical ... | 251 | COVID-19;Infections;Pneumonia;Pneumonia, Viral | null | null | Coronavirus Infections;Occupational Groups;Health Care;Algorithms;Transfer Learning;Sensitivity and Specificity;Polymerase Chain Reaction;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2004.09803 | null | Yes | null | null | 2,020 | 2020-04-21 | Preprint | arXiv | 0 | covidaid: covid-19 detection using chest x-ray | The exponential increase in COVID-19 patients is overwhelming healthcare systems across the world. With limited testing kits, it is impossible for every patient with respiratory illness to be tested using conventional techniques (RT-PCR). The tests also have long turn-around time, and limited sensitivity. Detecting pos... | 251 | COVID-19;Infections | null | null | Health Care;Polymerase Chain Reaction;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33091743 | 10.1016/j.media.2020.101844 | Yes | PMC7553063 | 33,091,743 | 2,020 | 2020-10-23 | Journal Article;Research Support, N.I.H., Extramural | Peer reviewed (PubMed) | 1 | integrative analysis for covid-19 patient outcome prediction | While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been intensively studied, little work has been performed for image-based patient outcome prediction. Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of pati... | 251 | COVID-19;Disease Progression;Lung Diseases;Pneumonia | 38 | Med Image Anal | Predictive Value;COVID-19 Testing;Polymerase Chain Reaction;Area under Curve;Reverse Transcription | 0.000003 | 41.608 | 0.000003 | 131 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | CT |
33821166 | 10.1016/j.bspc.2021.102588 | Yes | PMC8011666 | 33,821,166 | 2,021 | 2021-04-07 | Journal Article | Peer reviewed (PubMed) | 1 | a fully automated deep learning-based network for detecting covid-19 from a new and large lung ct scan dataset | This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's chest CT scan images. We introduce a new dataset that contains 48,260 CT scan images from 282 normal persons and 15,589 images from 95 patients with COVID-19 infections. At the first stage, this system runs... | 251 | COVID-19;Infections | 84 | Biomed Signal Process Control | Other Topics | 0.000002 | 68.68 | 0.000004 | 143 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33328512 | 10.1038/s41598-020-79097-1 | Yes | PMC7745019 | 33,328,512 | 2,020 | 2020-12-18 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | prediction of disease progression in patients with covid-19 by artificial intelligence assisted lesion quantification | To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT for prediction of disease progression and clinical outcome in patients with coronavirus disease 2019 (COVID-19). Patients with confirmed COVID-19 infection and initially of non-severe type were retrospectively included.... | 252 | COVID-19;Disease Progression;Infections | 12 | Sci Rep | Severity of Illness Index;ROC Curve;Retrospective Studies;Lung Diseases;Age | 0.000003 | 64.152 | 0.000003 | 191 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | CT |
2012.05073 | null | Yes | null | null | 2,020 | 2020-12-17 | Preprint | arXiv | 0 | covid-19 detection in chest x-ray images using a new channel boosted cnn | COVID-19 is a highly contagious respiratory infection that has affected a large population across the world and continues with its devastating consequences. It is imperative to detect COVID-19 at the earliest to limit the span of infection. In this work, a new classification technique CB-STM-RENet based on deep Convolu... | 253 | COVID-19;Infections;Respiratory Tract Infections | null | null | Transfer Learning;Architecture | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33164982 | 10.3233/XST-200735 | Yes | PMC7990455 | 33,164,982 | 2,020 | 2020-11-10 | Journal Article;Research Support, N.I.H., Intramural;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | using artificial intelligence to assist radiologists in distinguishing covid-19 from other pulmonary infections | Accurate and rapid diagnosis of coronavirus disease (COVID-19) is crucial for timely quarantine and treatment. In this study, a deep learning algorithm-based AI model using ResUNet network was developed to evaluate the performance of radiologists with and without AI assistance in distinguishing COVID-19 infected pneumo... | 253 | COVID-19;Infections;Pneumonia;Pneumonia, Viral;Tuberculosis | 11 | J Xray Sci Technol | Coronavirus Infections;Algorithms;ROC Curve;Lung Diseases;Age | 0.000005 | 198.48 | 0.00001 | 446 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32837679 | 10.1016/j.irbm.2020.07.001 | Yes | PMC7333623 | 32,837,679 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | automated deep transfer learning-based approach for detection of covid-19 infection in chest x-rays | The most widely used novel coronavirus (COVID-19) detection technique is a real-time polymerase chain reaction (RT-PCR). However, RT-PCR kits are costly and take 6-9 hours to confirm infection in the patient. Due to less sensitivity of RT-PCR, it provides high false-negative results. To resolve this problem, radiologic... | 253 | COVID-19;Infections | 98 | Ing Rech Biomed | Coronavirus Infections;Transfer Learning;Polymerase Chain Reaction;Tomography;Real-Time Polymerase Chain Reaction | 0.000004 | 75.088 | 0.000005 | 192 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32804113 | 10.3233/XST-200720 | Yes | PMC7592683 | 32,804,113 | 2,020 | 2020-08-18 | Comparative Study;Journal Article | Peer reviewed (PubMed) | 1 | detection of coronavirus disease from x-ray images using deep learning and transfer learning algorithms | This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of novel coronavirus (COVID-19) infected disease. This study applied transfer learning method to develop deep learning models for detecting COVID-19 di... | 253 | COVID-19;Pneumonia | 18 | J Xray Sci Technol | Coronavirus Infections;Art;Transfer Learning;Algorithms;Lung;Neural Networks;Tomography;Lung Diseases;Early Diagnosis | 0.000016 | 446.272 | 0.000026 | 1,092 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33162872 | 10.1016/j.asoc.2020.106859 | Yes | PMC7598372 | 33,162,872 | 2,020 | 2020-11-10 | Journal Article | Peer reviewed (PubMed) | 1 | instacovnet-19: a deep learning classification model for the detection of covid-19 patients using chest x-ray | Recently, the whole world became infected by the newly discovered coronavirus (COVID-19). SARS-CoV-2, or widely known as COVID-19, has proved to be a hazardous virus severely affecting the health of people. It causes respiratory illness, especially in people who already suffer from other diseases. Limited availability ... | 253 | COVID-19;Pneumonia | 66 | Appl Soft Comput | Other Topics | 0.000004 | 64.128 | 0.000005 | 170 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32427924 | 10.1038/s41591-020-0931-3 | Yes | PMC7446729 | 32,427,924 | 2,020 | 2020-05-20 | Journal Article;Research Support, N.I.H., Extramural;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | artificial intelligence-enabled rapid diagnosis of patients with covid-19 | For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currentl... | 254 | COVID-19 | 412 | Nat Med | Coronavirus Infections;Predictive Value;Polymerase Chain Reaction;Real-Time Polymerase Chain Reaction | 0.00001 | 222.112 | 0.000011 | 608 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33171999 | 10.3390/jcm9113576 | Yes | PMC7694629 | 33,171,999 | 2,020 | 2020-11-12 | Journal Article | Peer reviewed (PubMed) | 1 | accuracy of conventional and machine learning enhanced chest radiography for the assessment of covid-19 pneumonia: intra-individual comparison with ct | To evaluate diagnostic accuracy of conventional radiography (CXR) and machine learning enhanced CXR (mlCXR) for the detection and quantification of disease-extent in COVID-19 patients compared to chest-CT. Real-time polymerase chain reaction (rt-PCR)-confirmed COVID-19-patients undergoing CXR from March to April 2020 t... | 254 | COVID-19;Pneumonia | 3 | J Clin Med | Polymerase Chain Reaction;Real-Time Polymerase Chain Reaction | 0.000001 | 14.712 | 0.000001 | 43 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | Multimodal |
2006.13873 | null | Yes | null | null | 2,020 | 2020-06-18 | Preprint | arXiv | 0 | covidlite: a depth-wise separable deep neural network with white balance and clahe for detection of covid-19 | Currently, the whole world is facing a pandemic disease, novel Coronavirus also known as COVID-19, which spread in more than 200 countries with around 3.3 million active cases and 4.4 lakh deaths approximately. Due to rapid increase in number of cases and limited supply of testing kits, availability of alternative diag... | 255 | COVID-19;Death;Pneumonia, Viral | null | null | Art;Radiologists;Other Topics;Entropy | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2004.12592 | null | Yes | null | null | 2,020 | 2020-05-21 | Preprint | arXiv | 0 | robust screening of covid-19 from chest x-ray via discriminative cost-sensitive learning | This paper addresses the new problem of automated screening of coronavirus disease 2019 (COVID-19) based on chest X-rays, which is urgently demanded toward fast stopping the pandemic. However, robust and accurate screening of COVID-19 from chest X-rays is still a globally recognized challenge because of two bottlenecks... | 255 | COVID-19;Pneumonia;Pneumonia, Viral | null | null | Art;Algorithms | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33250662 | 10.1007/s00500-020-05424-3 | Yes | PMC7679792 | 33,250,662 | 2,020 | 2020-12-01 | Journal Article | Peer reviewed (PubMed) | 1 | covid-chexnet: hybrid deep learning framework for identifying covid-19 virus in chest x-rays images | The outbreaks of Coronavirus (COVID-19) epidemic have increased the pressure on healthcare and medical systems worldwide. The timely diagnosis of infected patients is a critical step to limit the spread of the COVID-19 epidemic. The chest radiography imaging has shown to be an effective screening technique in diagnosin... | 255 | COVID-19 | 56 | Soft comput | Radiography;Health Care;Transfer Learning;Architecture;Disease Outbreaks;Noise;Sensitivity and Specificity;Radiologists | 0.000003 | 68.344 | 0.000005 | 159 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32969949 | 10.1097/RTI.0000000000000559 | Yes | null | 32,969,949 | 2,020 | 2020-09-25 | Journal Article | Peer reviewed (PubMed) | 1 | detection of covid-19 using deep learning algorithms on chest radiographs | To evaluate the performance of a deep learning (DL) algorithm for the detection of COVID-19 on chest radiographs (CXR). In this retrospective study, a DL model was trained on 112,120 CXR images with 14 labeled classifiers (ChestX-ray14) and fine-tuned using initial CXR on hospital admission of 509 patients, who had und... | 256 | COVID-19;Fever;Pneumonia | 4 | J Thorac Imaging | Health Care;Sensitivity and Specificity;Polymerase Chain Reaction;Radiologists;Retrospective Studies;Area under Curve;Receiver Operating Characteristic | 0.000003 | 71.232 | 0.000004 | 188 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.05.11.20097907 | 10.1101/2020.05.11.20097907 | Yes | null | null | 2,020 | 2020-05-29 | Preprint | medRxiv | 0 | online covid-19 diagnosis with chest ct images: lesion-attention deep neural networks | Chest computed tomography (CT) scanning is one of the most important technologies for COVID-19 diagnosis and disease monitoring, particularly for early detection of coronavirus. Recent advancements in computer vision motivate more concerted efforts in developing AI-driven diagnostic tools to accommodate the enormous de... | 257 | COVID-19 | null | null | Diagnostic Tests;COVID-19 Testing | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
2008.09866 | null | Yes | null | null | 2,020 | 2020-08-22 | Preprint | arXiv | 0 | symbolic semantic segmentation and interpretation of covid-19 lung infections in chest ct volumes based on emergent languages | The coronavirus disease (COVID-19) has resulted in a pandemic crippling the a breadth of services critical to daily life. Segmentation of lung infections in computerized tomography (CT) slices could be be used to improve diagnosis and understanding of COVID-19 in patients. Deep learning systems lack interpretability be... | 257 | COVID-19;Infections | null | null | Coronavirus Infections;Art;Pandemics;Architecture;Semantics;Tomography;Lung Diseases;Masks;Cone-Beam Computed Tomography | null | null | null | null | null | External | Segmentation-only | CT |
34735458 | 10.1371/journal.pone.0258760 | Yes | PMC8568139 | 34,735,458 | 2,021 | 2021-11-05 | Journal Article | Peer reviewed (PubMed) | 1 | accuracy of deep learning-based computed tomography diagnostic system for covid-19: a consecutive sampling external validation cohort study | Ali-M3, an artificial intelligence program, analyzes chest computed tomography (CT) and detects the likelihood of coronavirus disease (COVID-19) based on scores ranging from 0 to 1. However, Ali-M3 has not been externally validated. Our aim was to evaluate the accuracy of Ali-M3 for detecting COVID-19 and discuss its c... | 257 | COVID-19;Infections | 2 | PLoS One | Coronavirus Infections;Reproducibility of Results;COVID-19 Testing;Reverse Transcription;Health Care;Image Processing;Sensitivity and Specificity;Polymerase Chain Reaction;ROC Curve;Retrospective Studies;Area under Curve;Age;Cohort Studies | 0.000001 | 33.88 | 0.000002 | 77 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
10.1101/2020.07.13.20152231 | 10.1101/2020.07.13.20152231 | Yes | null | null | 2,020 | 2020-10-16 | Preprint | medRxiv | 0 | a quantitative lung computed tomography image feature for multi-center severity assessment of covid-19 | The COVID-19 pandemic has affected millions and congested healthcare systems globally. Hence an objective severity assessment is crucial in making therapeutic decisions judiciously. Computed Tomography (CT)-scans can provide demarcating features to identify severity of pneumonia , commonly associated with COVID-19, in ... | 258 | COVID-19;COVID-19 Pandemic;Pneumonia | null | null | Health Care;Sensitivity and Specificity;Other Topics;ROC Curve | null | null | null | null | null | External | 3. Monitoring/Severity assessment | CT |
33191476 | 10.1007/s11548-020-02286-w | Yes | PMC7667011 | 33,191,476 | 2,020 | 2020-11-17 | Evaluation Study;Journal Article | Peer reviewed (PubMed) | 1 | automated detection of covid-19 using ensemble of transfer learning with deep convolutional neural network based on ct scans | COVID-19 has infected millions of people worldwide. One of the most important hurdles in controlling the spread of this disease is the inefficiency and lack of medical tests. Computed tomography (CT) scans are promising in providing accurate and fast detection of COVID-19. However, determining COVID-19 requires highly ... | 258 | COVID-19;Lung Diseases | 51 | Int J Comput Assist Radiol Surg | Transfer Learning;Architecture;COVID-19 Testing;Sensitivity and Specificity;Lung;Neural Networks;Tomography;Paper;ROC Curve;Lung Diseases | 0.000007 | 229.128 | 0.000016 | 483 | 0 | External | 2. Detection/Diagnosis | CT |
32992136 | 10.1016/j.ijmedinf.2020.104284 | Yes | PMC7510591 | 32,992,136 | 2,020 | 2020-09-30 | Journal Article;Research Support, N.I.H., Extramural | Peer reviewed (PubMed) | 1 | improving the performance of cnn to predict the likelihood of covid-19 using chest x-ray images with preprocessing algorithms | This study aims to develop and test a new computer-aided diagnosis (CAD) scheme of chest X-ray images to detect coronavirus (COVID-19) infected pneumonia. CAD scheme first applies two image preprocessing steps to remove the majority of diaphragm regions, process the original image using a histogram equalization algorit... | 259 | COVID-19;Infections;Pneumonia | 93 | Int J Med Inform | Coronavirus Infections;Transfer Learning;Algorithms;Sensitivity and Specificity;Neural Networks;Tomography | 0.000015 | 409.784 | 0.000025 | 961 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32568675 | 10.1016/j.compbiomed.2020.103792 | Yes | PMC7187882 | 32,568,675 | 2,020 | 2020-06-23 | Evaluation Study;Journal Article | Peer reviewed (PubMed) | 1 | automated detection of covid-19 cases using deep neural networks with x-ray images | The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic. It has caused a devastating effect on both daily lives, public health, and the global economy. It is critical to detect the positive cases as early as possible so... | 260 | COVID-19;Pneumonia | 752 | Comput Biol Med | Coronavirus Infections;Public Health;Neural Networks | 0.000016 | 429.48 | 0.000024 | 1,081 | 0 | External | 2. Detection/Diagnosis | X-Ray |
34194484 | 10.1155/2021/8828404 | Yes | PMC8203406 | 34,194,484 | 2,021 | 2021-07-02 | Journal Article | Peer reviewed (PubMed) | 1 | transfer learning to detect covid-19 automatically from x-ray images using convolutional neural networks | The novel coronavirus disease 2019 (COVID-19) is a contagious disease that has caused thousands of deaths and infected millions worldwide. Thus, various technologies that allow for the fast detection of COVID-19 infections with high accuracy can offer healthcare professionals much-needed help. This study is aimed at ev... | 261 | COVID-19;Death;Infections;Pneumonia, Viral | 30 | Int J Biomed Imaging | Art;Health Care;Algorithms;Transfer Learning;Sensitivity and Specificity | 0.000003 | 129.6 | 0.000008 | 272 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32730214 | 10.1109/TMI.2020.3001810 | Yes | PMC8769013 | 32,730,214 | 2,020 | 2020-07-31 | Journal Article | Peer reviewed (PubMed) | 1 | a rapid accurate and machine-agnostic segmentation and quantification method for ct-based covid-19 diagnosis | COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in developing diagnosis, prognosis and treatment strategies to combat the disease. Although nucleic acid detection has been mainly used as the gold standard to confirm this RN... | 261 | COVID-19;Infections | 69 | IEEE Trans Med Imaging | Coronavirus Infections;Art;Algorithms;Tomography;Lung Diseases | 0.000004 | 69.496 | 0.000005 | 201 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
2009.08831 | null | Yes | null | null | 2,020 | 2020-09-14 | Preprint | arXiv | 0 | fused deep convolutional neural network for precision diagnosis of covid-19 using chest x-ray images | With a Coronavirus disease (COVID-19) case count exceeding 10 million worldwide, there is an increased need for a diagnostic capability. The main variables in increasing diagnostic capability are reduced cost, turnaround or diagnosis time, and upfront equipment cost and accessibility. Two candidates for machine learnin... | 262 | COVID-19 | null | null | Art;Algorithms;Architecture;Tomography | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2005.01468 | null | Yes | null | null | 2,020 | 2020-05-01 | Preprint | arXiv | 0 | a cascade network for detecting covid-19 using chest x-rays | The worldwide spread of pneumonia caused by a novel coronavirus poses an unprecedented challenge to the world's medical resources and prevention and control measures. Covid-19 attacks not only the lungs, making it difficult to breathe and life-threatening, but also the heart, kidneys, brain and other vital organs of th... | 263 | COVID-19;Infections;Pneumonia;Pneumonia, Viral | null | null | Coronavirus Infections;Disease Outbreaks;Polymerase Chain Reaction;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2005.01903 | null | Yes | null | null | 2,020 | 2020-05-04 | Preprint | arXiv | 0 | 3d tomographic pattern synthesis for enhancing the quantification of covid-19 | The Coronavirus Disease (COVID-19) has affected 1.8 million people and resulted in more than 110,000 deaths as of April 12, 2020. Several studies have shown that tomographic patterns seen on chest Computed Tomography (CT), such as ground-glass opacities, consolidations, and crazy paving pattern, are correlated with the... | 263 | COVID-19;Communicable Diseases;Death | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
33201872 | 10.24875/RIC.20000451 | Yes | null | 33,201,872 | 2,020 | 2020-11-18 | Journal Article | Peer reviewed (PubMed) | 1 | validation of chest computed tomography artificial intelligence to determine the requirement for mechanical ventilation and risk of mortality in hospitalized coronavirus disease-19 patients in a tertiary care center in mexico city | Artificial intelligence (AI) in radiology has improved diagnostic performance and shortened reading times of coronavirus disease 2019 (COVID-19) patients' studies. The objectives pf the study were to analyze the performance of a chest computed tomography (CT) AI quantitative algorithm for determining the risk of mortal... | 263 | COVID-19 | 12 | Rev Invest Clin | Algorithms;ROC Curve;Ventilation | 0.000002 | 21.696 | 0.000002 | 54 | 0 | Self-recorded/clinical | 1. Risk identification | CT |
2003.11055 | null | Yes | null | null | 2,020 | 2020-03-24 | Preprint | arXiv | 0 | covidx-net: a framework of deep learning classifiers to diagnose covid-19 in x-ray images | Background and Coronaviruses (CoV) are perilous viruses that may cause Severe Acute Respiratory Syndrome (SARS-CoV), Middle East Respiratory Syndrome (MERS-CoV). The novel 2019 Coronavirus disease (COVID-19) was discovered as a novel disease pneumonia in the city of Wuhan, China at the end of 2019. Now, it becomes a Co... | 265 | COVID-19;Death;Middle East Respiratory Syndrome;Pneumonia;Severe Acute Respiratory Syndrome | null | null | World Health Organization;Architecture;Disease Outbreaks;Radiologists;Neural Networks | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
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