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2012.05525 | null | Yes | null | null | 2,020 | 2020-12-10 | Preprint | arXiv | 0 | detection of covid-19 patients with convolutional neural network based features on multi-class x-ray chest images | Covid-19 is a very serious deadly disease that has been announced as a pandemic by the world health organization (WHO). The whole world is working with all its might to end Covid-19 pandemic, which puts countries in serious health and economic problems, as soon as possible. The most important of these is to correctly i... | 194 | COVID-19;COVID-19 Pandemic | null | null | World Health Organization;Polymerase Chain Reaction;Neural Networks;Support Vector Machine;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2011.14871 | null | Yes | null | null | 2,020 | 2020-11-30 | Preprint | arXiv | 0 | vidi: descriptive visual data clustering as radiologist assistant in covid-19 streamline diagnostic | In the light of the COVID-19 pandemic, deep learning methods have been widely investigated in detecting COVID-19 from chest X-rays. However, a more pragmatic approach to applying AI methods to a medical diagnosis is designing a framework that facilitates human-machine interaction and expert decision making. Studies hav... | 195 | COVID-19;COVID-19 Pandemic;Pneumonia | null | null | Proteins;Other Topics;Map;Cluster Analysis | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.05.12.20099937 | 10.1101/2020.05.12.20099937 | Yes | null | null | 2,020 | 2020-05-14 | Preprint | medRxiv | 0 | deep transfer learning-based covid-19 prediction using chest x-rays | The novel coronavirus disease (COVID-19) is spreading very rapidly across the globe because of its highly contagious nature, and is declared as a pandemic by world health organization (WHO). Scientists are endeavoring to ascertain the drugs for its efficacious treatment. Because, till now, no full-proof drug is availab... | 195 | COVID-19 | null | null | World Health Organization;Transfer Learning;Other Topics;Pharmaceutical Preparations | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2006.11988 | null | Yes | null | null | 2,020 | 2020-12-14 | Preprint | arXiv | 0 | covid-19 image data collection: prospective predictions are the future | Across the world's coronavirus disease 2019 (COVID-19) hot spots, the need to streamline patient diagnosis and management has become more pressing than ever. As one of the main imaging tools, chest X-rays (CXRs) are common, fast, non-invasive, relatively cheap, and potentially bedside to monitor the progression of the ... | 196 | COVID-19 | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | Multimodal |
33275588 | 10.1109/JBHI.2020.3042523 | Yes | PMC8545178 | 33,275,588 | 2,020 | 2020-12-05 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | covid-19 ct image synthesis with a conditional generative adversarial network | Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread rapidly since December 2019. Real-time reverse transcription polymerase chain reaction (rRT-PCR) and chest computed tomography (CT) imaging both play an important role in COVID-19 diagnosis. Chest CT imaging offers the benefits of quick r... | 196 | COVID-19;Infections | 33 | IEEE J Biomed Health Inform | Radiography;Magnetic Resonance Imaging;Art;Pandemics;Semantics;Lung;Polymerase Chain Reaction;Classification;Tomography;Lung Diseases;Reverse Transcription | 0.000003 | 93.68 | 0.000005 | 220 | 0 | External | 5. Post-hoc | CT |
2007.08028 | null | Yes | PMC7373136 | 32,699,815 | 2,021 | 2021-07-01 | Preprint | arXiv | 0 | predicting clinical outcomes in covid-19 using radiomics and deep learning on chest radiographs: a multi-institutional study | We predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-center, retrospective study analyzed 530 deidentified CXRs from 515 COVID-19 patients treated at Stony Brook University Hospital and Newark Beth... | 197 | COVID-19;COVID-19 Pandemic | null | null | Classification;Other Topics;Retrospective Studies;Area under Curve | 0.000002 | 30.896 | 0.000002 | 72 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | X-Ray |
10.1101/2020.08.24.20181339 | 10.1101/2020.08.24.20181339 | Yes | null | null | 2,021 | 2021-08-09 | Preprint | medRxiv | 0 | diagnosis of covid-19 from x-rays using combined cnn-rnn architecture with transfer learning | The confrontation of COVID-19 pandemic has become one of the promising challenges of the world healthcare. Accurate and fast diagnosis of COVID-19 cases is essential for correct medical treatment to control this pandemic. Compared with the reverse-transcription polymerase chain reaction (RT-PCR) method, chest radiograp... | 197 | COVID-19;COVID-19 Pandemic | null | null | Health Care;Transfer Learning;Architecture;Polymerase Chain Reaction;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.07.16.20155093 | 10.1101/2020.07.16.20155093 | Yes | null | null | 2,020 | 2020-11-06 | Preprint | medRxiv | 0 | automated covid-19 detection from frontal chest x-ray images using deep learning: an online feasibility study | to evaluate the performance of Deep Learning methods to detect covid-19 from X-Ray chest images Chest X-Ray (CXR) images collected from confirmed covid-19 cases in several different centers and institutions and available online were downloaded and combined together with images of healthy patients and patients suffering... | 197 | COVID-19;Pneumonia, Bacterial | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33360271 | 10.1016/j.compbiomed.2020.104181 | Yes | PMC7831681 | 33,360,271 | 2,020 | 2020-12-29 | Journal Article | Peer reviewed (PubMed) | 1 | lightweight deep learning models for detecting covid-19 from chest x-ray images | Deep learning methods have already enjoyed an unprecedented success in medical imaging problems. Similar success has been evidenced when it comes to the detection of COVID-19 from medical images, therefore deep learning approaches are considered good candidates for detecting this disease, in collaboration with radiolog... | 197 | COVID-19;Pneumonia, Bacterial | 43 | Comput Biol Med | Other Topics | 0.000003 | 64.416 | 0.000005 | 148 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32305937 | 10.1109/RBME.2020.2987975 | Yes | null | 32,305,937 | 2,020 | 2020-04-20 | Journal Article;Review | Peer reviewed (PubMed) | 1 | review of artificial intelligence techniques in imaging data acquisition segmentation and diagnosis for covid-19 | The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world. Medical imaging such as X-ray and computed tomography (CT) plays an essential role in the global fight against COVID-19, whereas the recently emerging artificial intelligence (AI) technologies further strengthen the power of the imagin... | 197 | COVID-19;Infections | 423 | IEEE Rev Biomed Eng | Other Topics | 0.000005 | 178.64 | 0.000009 | 406 | 0 | External | Review | Multimodal |
2006.13817 | null | Yes | null | null | 2,020 | 2020-06-22 | Preprint | arXiv | 0 | stacked convolutional neural network for diagnosis of covid-19 disease from x-ray images | Automatic and rapid screening of COVID-19 from the chest X-ray images has become an urgent need in this pandemic situation of SARS-CoV-2 worldwide in 2020. However, accurate and reliable screening of patients is a massive challenge due to the discrepancy between COVID-19 and other viral pneumonia in X-ray images. In th... | 198 | COVID-19;Pneumonia;Pneumonia, Viral | null | null | Neural Networks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
34175533 | 10.1016/j.compbiomed.2021.104605 | Yes | PMC8219713 | 34,175,533 | 2,021 | 2021-06-28 | Journal Article;Review | Peer reviewed (PubMed) | 1 | medical imaging and computational image analysis in covid-19 diagnosis: a review | Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough, and chronic fatigue, amongst others. The disease may be asymptomatic in some patients in the early stages, which can lead to increased trans... | 198 | COVID-19;Communicable Diseases;Cough;Dyspnea;Fatigue;Fever | 5 | Comput Biol Med | COVID-19 Testing;Image Processing;Paper | 0.000001 | 34.36 | 0.000002 | 75 | 0 | N.A. | Review | Multimodal |
2005.03059 | null | Yes | null | null | 2,020 | 2020-05-15 | Preprint | arXiv | 0 | covidctnet: an open-source deep learning approach to identify covid-19 using ct image | Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase polymerase chain reaction (RT-PCR) is the gold standard of outpa... | 198 | COVID-19;Lung Diseases;Pneumonia | null | null | Polymerase Chain Reaction;Other Topics | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33649695 | 10.1007/s00521-020-05641-9 | Yes | PMC7905772 | 33,649,695 | 2,021 | 2021-03-03 | Journal Article | Peer reviewed (PubMed) | 1 | triage of potential covid-19 patients from chest x-ray images using hierarchical convolutional networks | The current COVID-19 pandemic has motivated the researchers to use artificial intelligence techniques for a potential alternative to reverse transcription-polymerase chain reaction due to the limited scale of testing. The chest X-ray (CXR) is one of the alternatives to achieve fast diagnosis, but the unavailability of ... | 199 | COVID-19;COVID-19 Pandemic | 11 | Neural Comput Appl | Research Personnel;Polymerase Chain Reaction;Reverse Transcription | 0.000002 | 28.6 | 0.000002 | 61 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33967366 | 10.1016/j.bbe.2021.04.006 | Yes | PMC8084624 | 33,967,366 | 2,021 | 2021-05-11 | Journal Article | Peer reviewed (PubMed) | 1 | automated detection of covid-19 from ct scans using convolutional neural networks | Under the prevailing circumstances of the global pandemic of COVID-19, early diagnosis and accurate detection of COVID-19 through tests/screening and, subsequently, isolation of the infected people would be a proactive measure. Artificial intelligence (AI) based solutions, using Convolutional Neural Network (CNN) and e... | 199 | COVID-19;Pneumonia | 18 | Biocybern Biomed Eng | Algorithms;Transfer Learning;Architecture | 0.000002 | 69.92 | 0.000005 | 140 | 0 | External | 2. Detection/Diagnosis | CT |
2006.05274 | null | Yes | null | null | 2,020 | 2020-06-06 | Preprint | arXiv | 0 | umls-chestnet: a deep convolutional neural network for radiological findings differential diagnoses and localizations of covid-19 in chest x-rays | In this work we present a method for the detection of radiological findings, their location and differential diagnoses from chest x-rays. Unlike prior works that focus on the detection of few pathologies, we use a hierarchical taxonomy mapped to the Unified Medical Language System (UMLS) terminology to identify 189 rad... | 199 | COVID-19 | null | null | Polymerase Chain Reaction;Area under Curve | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
2004.00038 | null | Yes | null | null | 2,020 | 2020-03-31 | Preprint | arXiv | 0 | diagnosing covid-19 pneumonia from x-ray and ct images using deep learning and transfer learning algorithms | COVID-19 (also known as 2019 Novel Coronavirus) first emerged in Wuhan, China and spread across the globe with unprecedented effect and has now become the greatest crisis of the modern era. The COVID-19 has proved much more pervasive demands for diagnosis that has driven researchers to develop more intelligent, highly ... | 199 | COVID-19;Pneumonia | null | null | Health Care;Algorithms;Transfer Learning;Research Personnel | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
2004.02060 | null | Yes | null | null | 2,020 | 2020-05-20 | Preprint | arXiv | 0 | finding covid-19 from chest x-rays using deep learning on a small dataset | Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for diagnosis quickly. This paper explores how useful chest X-ray images can be in dia... | 199 | COVID-19;Pneumonia;Pneumonia, Bacterial | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2009.05436 | null | Yes | null | null | 2,021 | 2021-02-28 | Preprint | arXiv | 0 | semi-supervised active learning for covid-19 lung ultrasound multi-symptom classification | Ultrasound (US) is a non-invasive yet effective medical diagnostic imaging technique for the COVID-19 global pandemic. However, due to complex feature behaviors and expensive annotations of US images, it is difficult to apply Artificial Intelligence (AI) assisting approaches for lung's multi-symptom (multi-label) class... | 200 | COVID-19 | null | null | Diagnostic Imaging;Art;Other Topics;Map | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | Ultrasound |
2010.16043 | null | Yes | null | null | 2,020 | 2020-10-29 | Preprint | arXiv | 0 | ct-caps: feature extraction-based automated framework for covid-19 disease identification from chest ct scans using capsule networks | The global outbreak of the novel corona virus (COVID-19) disease has drastically impacted the world and led to one of the most challenging crisis across the globe since World War II. The early diagnosis and isolation of COVID-19 positive cases are considered as crucial steps towards preventing the spread of the disease... | 200 | COVID-19 | null | null | Art;Disease Outbreaks;Polymerase Chain Reaction;Tomography;Early Diagnosis;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
33729944 | 10.1109/TCBB.2021.3066331 | Yes | PMC9647721 | 33,729,944 | 2,021 | 2021-03-18 | Journal Article | Peer reviewed (PubMed) | 1 | soda: detecting covid-19 in chest x-rays with semi-supervised open set domain adaptation | Due to the shortage of COVID-19 viral testing kits, radiology is used to complement the screening process. Deep learning methods are promising in automatically detecting COVID-19 disease in chest x-ray images. Most of these works first train a Convolutional Neural Network (CNN) on an existing large-scale chest x-ray im... | 200 | COVID-19;Pneumonia | 9 | IEEE/ACM Trans Comput Biol Bioinform | Art;Other Topics | 0.000001 | 30.52 | 0.000002 | 65 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33192206 | 10.1016/j.asoc.2020.106885 | Yes | PMC7647900 | 33,192,206 | 2,020 | 2020-11-17 | Journal Article | Peer reviewed (PubMed) | 1 | the ensemble deep learning model for novel covid-19 on ct images | The rapid detection of the novel coronavirus disease, COVID-19, has a positive effect on preventing propagation and enhancing therapeutic outcomes. This article focuses on the rapid detection of COVID-19. We propose an ensemble deep learning model for novel COVID-19 detection from CT images. 2933 lung CT images from CO... | 200 | COVID-19;Neoplasms | 80 | Appl Soft Comput | Transfer Learning;Algorithms;Sensitivity and Specificity;Lung;Neural Networks | 0.000005 | 70.456 | 0.000006 | 165 | 0 | External | 2. Detection/Diagnosis | CT |
33015100 | 10.3389/fmed.2020.00550 | Yes | PMC7461795 | 33,015,100 | 2,020 | 2020-10-06 | Journal Article | Peer reviewed (PubMed) | 1 | the performance of deep neural networks in differentiating chest x-rays of covid-19 patients from other bacterial and viral pneumonias | Chest radiography is a critical tool in the early detection, management planning, and follow-up evaluation of COVID-19 pneumonia; however, in smaller clinics around the world, there is a shortage of radiologists to analyze large number of examinations especially performed during a pandemic. Limited availability of high... | 200 | COVID-19;COVID-19 Pandemic;Disease Progression;Pneumonia;Pneumonia, Viral | 10 | Front Med (Lausanne) | Transfer Learning;Algorithms;Polymerase Chain Reaction;Tomography;Real-Time Polymerase Chain Reaction | 0.000003 | 35.472 | 0.000003 | 102 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.04.13.20063461 | 10.1101/2020.04.13.20063461 | Yes | null | null | 2,020 | 2020-04-17 | Preprint | medRxiv | 0 | accurate prediction of covid-19 using chest x-ray images through deep feature learning model with smote and machine learning classifiers | According to the World Health Organization (WHO), the coronavirus (COVID-19) pandemic is putting even the best healthcare systems across the world under tremendous pressure. The early detection of this type of virus will help in relieving the pressure of the healthcare systems. Chest X-rays has been playing a crucial r... | 202 | COVID-19;COVID-19 Pandemic;Influenza, Human;Pneumonia | null | null | World Health Organization;Health Care;Disease Outbreaks;Random Forest | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32719039 | 10.1136/annrheumdis-2020-218048 | Yes | PMC7456556 | 32,719,039 | 2,020 | 2020-07-29 | Comparative Study;Journal Article | Peer reviewed (PubMed) | 1 | lung involvement in macrophage activation syndrome and severe covid-19: results from a cross-sectional study to assess clinical laboratory and artificial intelligence-radiological differences | To evaluate the clinical pictures, laboratory tests and imaging of patients with lung involvement, either from severe COVID-19 or macrophage activation syndrome (MAS), in order to assess how similar these two diseases are. The present work has been designed as a cross-sectional single-centre study to compare characteri... | 202 | COVID-19;Fever;Macrophage Activation Syndrome | 28 | Ann Rheum Dis | Coronavirus Infections;C-Reactive Protein;Retrospective Studies | 0.000003 | 30.552 | 0.000002 | 121 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
10.1101/2020.05.05.20091561 | 10.1101/2020.05.05.20091561 | Yes | null | null | 2,020 | 2020-05-08 | Preprint | medRxiv | 0 | ai based chest x-ray (cxr) scan texture analysis algorithm for digital test of covid-19 patients | Chest Imaging in COVID-19 patient management is becoming an essential tool for controlling the pandemic that is gripping the international community. It is already indicated in patients with COVID-19 and worsening respiratory status. The rapid spread of the pandemic to all continents, albeit with a nonuniform community... | 202 | Bacterial Infections;COVID-19;Infections | null | null | Health Care;Sensitivity and Specificity | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33362346 | 10.1002/ima.22525 | Yes | PMC7753711 | 33,362,346 | 2,020 | 2020-12-29 | Journal Article | Peer reviewed (PubMed) | 1 | an integrated feature frame work for automated segmentation of covid-19 infection from lung ct images | The novel coronavirus disease (SARS-CoV-2 or COVID-19) is spreading across the world and is affecting public health and the world economy. Artificial Intelligence (AI) can play a key role in enhancing COVID-19 detection. However, lung infection by COVID-19 is not quantifiable due to a lack of studies and the difficulty... | 202 | COVID-19;Infections | 14 | Int J Imaging Syst Technol | Coronavirus Infections;Art;Public Health;Algorithms;Tomography;Lung Diseases | 0.000002 | 44.856 | 0.000003 | 99 | 0 | External | Segmentation-only | CT |
32344309 | 10.1016/j.mehy.2020.109761 | Yes | PMC7179515 | 32,344,309 | 2,020 | 2020-04-29 | Journal Article | Peer reviewed (PubMed) | 1 | covidiagnosis-net: deep bayes-squeezenet based diagnosis of the coronavirus disease 2019 (covid-19) from x-ray images | The Coronavirus Disease 2019 (COVID-19) outbreak has a tremendous impact on global health and the daily life of people still living in more than two hundred countries. The crucial action to gain the force in the fight of COVID-19 is to have powerful monitoring of the site forming infected patients. Most of the initial ... | 203 | COVID-19 | 241 | Med Hypotheses | Coronavirus Infections;Disease Outbreaks;Image Processing;Neural Networks;Early Diagnosis | 0.000008 | 210.864 | 0.000012 | 544 | 0 | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.10.13.20212258 | 10.1101/2020.10.13.20212258 | Yes | null | null | 2,020 | 2020-10-22 | Preprint | medRxiv | 0 | development of a deep learning classifier to accurately distinguish covid-19 from look-a-like pathology on lung ultrasound | Lung ultrasound (LUS) is a portable, low cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning techniques to match or exceed human-level, diagnostic specificity among similar ap... | 203 | COVID-19;Pulmonary Edema;Respiratory Distress Syndrome, Acute | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | Ultrasound |
2004.03042 | null | Yes | null | null | 2,020 | 2020-09-07 | Preprint | arXiv | 0 | covid-mobilexpert: on-device covid-19 patient triage and follow-up using chest x-rays | During the COVID-19 pandemic, there has been an emerging need for rapid, dedicated, and point-of-care COVID-19 patient disposition techniques to optimize resource utilization and clinical workflow. In view of this need, we present COVID-MobileXpert: a lightweight deep neural network (DNN) based mobile app that can use ... | 204 | COVID-19;COVID-19 Pandemic;Lung Diseases;Pneumonia | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.07.11.20149112 | 10.1101/2020.07.11.20149112 | Yes | null | null | 2,020 | 2020-07-11 | Preprint | medRxiv | 0 | reconet: multi-level preprocessing of chest x-rays for covid-19 detection using convolutional neural networks | Life-threatening COVID-19 detection from radiomic features has become a dire need of the present time for infection control and socio-economic crisis management around the world. In this paper, a novel convolutional neural network (CNN) architecture, ReCoNet (residual image-based COVID-19 detection network), is propose... | 204 | COVID-19;Infections | null | null | Polymerase Chain Reaction;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2003.09439 | null | Yes | null | null | 2,020 | 2020-09-22 | Preprint | arXiv | 0 | roam: random layer mixup for semi-supervised learning in medical imaging | Medical image segmentation is one of the major challenges addressed by machine learning methods. Yet, deep learning methods profoundly depend on a large amount of annotated data, which is time-consuming and costly. Though, semi-supervised learning methods approach this problem by leveraging an abundant amount of unlabe... | 204 | COVID-19;Infections | null | null | Art;Other Topics | null | null | null | null | null | External | Segmentation-only | Multimodal |
2011.05746 | null | Yes | null | null | 2,020 | 2020-11-11 | Preprint | arXiv | 0 | classification of covid-19 in chest ct images using convolutional support vector machines | Coronavirus 2019 (COVID-19), which emerged in Wuhan, China and affected the whole world, has cost the lives of thousands of people. Manual diagnosis is inefficient due to the rapid spread of this virus. For this reason, automatic COVID-19 detection studies are carried out with the support of artificial intelligence alg... | 204 | COVID-19 | null | null | Transfer Learning;Algorithms;Tomography | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
32406829 | 10.1109/TMI.2020.2994459 | Yes | null | 32,406,829 | 2,020 | 2020-05-15 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning for classification and localization of covid-19 markers in point-of-care lung ultrasound | Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scans, this paper studies the application of DL techniques for the analysi... | 205 | COVID-19;COVID-19 Pandemic;Lung Diseases | 162 | IEEE Trans Med Imaging | Coronavirus Infections;Art;Point-of-Care Systems;Ultrasonography;Lung Diseases;Masks | 0.000005 | 82.184 | 0.000005 | 243 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | Ultrasound |
33518813 | 10.1016/j.patcog.2021.107826 | Yes | PMC7833525 | 33,518,813 | 2,021 | 2021-02-02 | Journal Article | Peer reviewed (PubMed) | 1 | momentum contrastive learning for few-shot covid-19 diagnosis from chest ct images | The current pandemic, caused by the outbreak of a novel coronavirus (COVID-19) in December 2019, has led to a global emergency that has significantly impacted economies, healthcare systems and personal wellbeing all around the world. Controlling the rapidly evolving disease requires highly sensitive and specific diagno... | 205 | COVID-19 | 42 | Pattern Recognit | Health Care;Disease Outbreaks;Polymerase Chain Reaction;Other Topics | 0.000002 | 41.88 | 0.000003 | 89 | 0 | External | 2. Detection/Diagnosis | CT |
2005.04562 | null | Yes | null | null | 2,020 | 2020-05-25 | Preprint | arXiv | 0 | fast and accurate detection of covid-19-related pneumonia from chest x-ray images with novel deep learning model | Novel coronavirus disease has spread rapidly worldwide. As recent radiological literatures on Covid-19 related pneumonia is primarily focused on CT findings, the American College of Radiology (ACR) recommends using portable chest X-radiograph (CXR). A tool to assist for detection and monitoring of Covid-19 cases from C... | 205 | COVID-19;Pneumonia | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32840070 | 10.7507/1001-5515.202005056 | Yes | null | 32,840,070 | 2,020 | 2020-08-26 | Journal Article | Peer reviewed (PubMed) | 1 | research on covid-19 detection method based on depthwise separable densenet in chest x-ray images | Coronavirus disease 2019 (COVID-19) has spread rapidly around the world. In order to diagnose COVID-19 more quickly, in this paper, a depthwise separable DenseNet was proposed. The paper constructed a deep learning model with 2 905 chest X-ray images as experimental dataset. In order to enhance the contrast, the contra... | 205 | COVID-19;Pneumonia | 2 | Sheng Wu Yi Xue Gong Cheng Xue Za Zhi | Other Topics | 0.000005 | 96.536 | 0.000006 | 263 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2012.14204 | null | Yes | null | null | 2,020 | 2020-12-29 | Preprint | arXiv | 0 | screening covid-19 based on ct/cxr images and building a publicly available ct-scan dataset of covid-19 | The rapid outbreak of COVID-19 threatens humans life all around the world. Due to insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. As chest radiography, such as chest X-ray (CXR) and CT computed tomography (CT), is a possible way ... | 206 | COVID-19 | null | null | Transfer Learning;Research Personnel;Disease Outbreaks;Tomography;Area under Curve | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32845849 | 10.1109/JBHI.2020.3019505 | Yes | null | 32,845,849 | 2,020 | 2020-08-28 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | adaptive feature selection guided deep forest for covid-19 classification with chest ct | Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, w... | 206 | COVID-19;Pneumonia | 67 | IEEE J Biomed Health Inform | Radiography;Coronavirus Infections;Disease Outbreaks;COVID-19 Testing;Sensitivity and Specificity;Neural Networks;Paper;Area under Curve | 0.000007 | 173.136 | 0.000009 | 472 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
34075355 | 10.1007/s42979-021-00695-5 | Yes | PMC8152712 | 34,075,355 | 2,021 | 2021-06-03 | Journal Article | Peer reviewed (PubMed) | 1 | chest x-ray classification using deep learning for automated covid-19 screening | In today's world, we find ourselves struggling to fight one of the worst pandemics in the history of humanity known as COVID-2019 caused by a coronavirus. When the virus reaches the lungs, we observe ground-glass opacity in the chest X-ray due to fibrosis in the lungs. Due to the significant differences between X-ray i... | 207 | COVID-19;Fibrosis;Infections;Pneumonia;Tuberculosis | 25 | SN Comput Sci | Tuberculosis;Fibrosis | 0.000001 | 40.36 | 0.000003 | 83 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
2009.01657 | null | Yes | null | null | 2,020 | 2020-08-27 | Preprint | arXiv | 0 | a free web service for fast covid-19 classification of chest x-ray images | The coronavirus outbreak became a major concern for society worldwide. Technological innovation and ingenuity are essential to fight COVID-19 pandemic and bring us one step closer to overcome it. Researchers over the world are working actively to find available alternatives in different fields, such as the Healthcare S... | 207 | COVID-19;COVID-19 Pandemic | null | null | Health Care;Research Personnel;Architecture;Disease Outbreaks | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2009.06116 | 10.3390/app11020672 | Yes | null | null | 2,020 | 2020-09-13 | Preprint | arXiv | 0 | accelerating covid-19 differential diagnosis with explainable ultrasound image analysis | Controlling the COVID-19 pandemic largely hinges upon the existence of fast, safe, and highly-available diagnostic tools. Ultrasound, in contrast to CT or X-Ray, has many practical advantages and can serve as a globally-applicable first-line examination technique. We provide the largest publicly available lung ultrasou... | 208 | COVID-19;COVID-19 Pandemic;Pneumonia, Bacterial | null | null | Specificity;Architecture;Map | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | Ultrasound |
2007.10785 | null | Yes | null | null | 2,020 | 2020-07-27 | Preprint | arXiv | 0 | automated detection and forecasting of covid-19 using deep learning techniques: a review | Coronavirus, or COVID-19, is a hazardous disease that has endangered the health of many people around the world by directly affecting the lungs. COVID-19 is a medium-sized, coated virus with a single-stranded RNA. This virus has one of the largest RNA genomes and is approximately 120 nm. The X-Ray and computed tomograp... | 210 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | Review | Multimodal |
2005.01578 | 10.1007/s42600-021-00132-9 | Yes | null | null | 2,021 | 2021-01-12 | Preprint | arXiv | 0 | a deep convolutional neural network for covid-19 detection using chest x-rays | We present image classifiers based on Dense Convolutional Networks and transfer learning to classify chest X-ray images according to three labels: COVID-19, pneumonia and normal. We fine-tuned neural networks pretrained on ImageNet and applied a twice transfer learning approach, using NIH ChestX-ray14 dataset as an int... | 210 | COVID-19;Pneumonia | null | null | Art;Transfer Learning;Other Topics | 0.000001 | 0 | 0.000001 | 0 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33705321 | 10.1109/TCBB.2021.3065361 | Yes | PMC8851430 | 33,705,321 | 2,021 | 2021-03-12 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | deep learning enables accurate diagnosis of novel coronavirus (covid-19) with ct images | A novel coronavirus (COVID-19) recently emerged as an acute respiratory syndrome, and has caused a pneumonia outbreak world-widely. As the COVID-19 continues to spread rapidly across the world, computed tomography (CT) has become essentially important for fast diagnoses. Thus, it is urgent to develop an accurate comput... | 211 | COVID-19;Pneumonia;Syndrome | 265 | IEEE/ACM Trans Comput Biol Bioinform | Disease Outbreaks;Area under Curve | 0.000003 | 131.56 | 0.000007 | 279 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
34492574 | 10.1016/j.media.2021.102216 | Yes | PMC8401374 | 34,492,574 | 2,021 | 2021-09-08 | Journal Article;Multicenter Study | Peer reviewed (PubMed) | 1 | aiforcovid: predicting the clinical outcomes in patients with covid-19 applying ai to chest-x-rays an italian multicentre study | Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this wor... | 211 | COVID-19;Death | 26 | Med Image Anal | Other Topics | 0.000001 | 21.4 | 0.000001 | 49 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | X-Ray |
32386147 | 10.1109/TMI.2020.2992546 | Yes | null | 32,386,147 | 2,020 | 2020-05-10 | Journal Article | Peer reviewed (PubMed) | 1 | diagnosis of coronavirus disease 2019 (covid-19) with structured latent multi-view representation learning | Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of infected patients and heavy labor for doctors, computer-aided diagnosis with machine learning algorithm is urgently needed, and could largely reduce the efforts of clinicians and accelerate the ... | 212 | COVID-19;Pneumonia | 94 | IEEE Trans Med Imaging | Coronavirus Infections;Disease Outbreaks | 0.000003 | 46.464 | 0.000003 | 150 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
10.1101/2020.08.13.20174144 | 10.1101/2020.08.13.20174144 | Yes | null | null | 2,020 | 2020-08-14 | Preprint | medRxiv | 0 | precise prediction of covid-19 in chest x-ray images using ke sieve algorithm | The novel coronavirus (COVID-19) pandemic is pressurizing the healthcare systems across the globe and few of them are on the verge of failing. The detection of this virus as early as possible will help in contaminating the spread of it as the virus is mutating itself as fast as possible and currently there are about 4,... | 212 | COVID-19;COVID-19 Pandemic;Infections;Influenza, Human;Pneumonia;Strains | null | null | Coronavirus Infections;Health Care | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33048773 | 10.1109/JBHI.2020.3030853 | Yes | null | 33,048,773 | 2,020 | 2020-10-14 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | m 3lung-sys: a deep learning system for multi-class lung pneumonia screening from ct imaging | To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic. Considering the limited training cases and resources (e.g, time and budget), we propose a Multi-task Multi-slice Deep Learning System (M... | 212 | COVID-19;Pneumonia | 21 | IEEE J Biomed Health Inform | Disease Outbreaks;Other Topics;Lung Diseases;Map;Cone-Beam Computed Tomography | 0.000002 | 22.912 | 0.000002 | 76 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33065387 | 10.1016/j.compbiomed.2020.104037 | Yes | PMC7543793 | 33,065,387 | 2,020 | 2020-10-17 | Journal Article | Peer reviewed (PubMed) | 1 | multi-task deep learning based ct imaging analysis for covid-19 pneumonia: classification and segmentation | This paper presents an automatic classification segmentation tool for helping screening COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess the severity of pneumonia and follow-up the patients. In this work, we propose a new multitask deep learning model to jointly identify COVID-19 pati... | 212 | COVID-19;Lung Cancer;Pneumonia | 171 | Comput Biol Med | Coronavirus Infections;Architecture;Neural Networks;ROC Curve | 0.000008 | 171.944 | 0.00001 | 439 | 0 | External | 2. Detection/Diagnosis | CT |
33449887 | 10.1109/JBHI.2021.3051470 | Yes | null | 33,449,887 | 2,021 | 2021-01-16 | Journal Article | Peer reviewed (PubMed) | 1 | distant domain transfer learning for medical imaging | Medical image processing is one of the most important topics in the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-art performances on medical imaging tasks. In this paper, we propose a novel transfer learning framework for medical image classification. Moreover, we app... | 213 | COVID-19 | 16 | IEEE J Biomed Health Inform | Art;Transfer Learning;Algorithms;Lung;Image Processing;Tomography;Lung Diseases | 0.000002 | 22.68 | 0.000002 | 57 | 0 | External | Segmentation-only | CT |
34192015 | 10.1136/bmjinnov-2020-000593 | Yes | PMC7931213 | 34,192,015 | 2,021 | 2021-07-01 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning model to predict the need for mechanical ventilation using chest x-ray images in hospitalised patients with covid-19 | There exists a wide gap in the availability of mechanical ventilator devices and their acute need in the context of the COVID-19 pandemic. An initial triaging method that accurately identifies the need for mechanical ventilation in hospitalised patients with COVID-19 is needed. We aimed to investigate if a potentially ... | 213 | COVID-19;COVID-19 Pandemic;Clinical Course | 8 | BMJ Innov | Other Topics | 0.000001 | 14.68 | 0.000001 | 33 | 0 | Self-recorded/clinical | 4. Prognosis/Treatment | X-Ray |
2007.15546 | null | Yes | null | null | 2,022 | 2022-01-10 | Preprint | arXiv | 0 | comparative study of deep learning methods for the automatic segmentation of lung lesion and lesion type in ct scans of covid-19 patients | Recent research on COVID-19 suggests that CT imaging provides useful information to assess disease progression and assist diagnosis, in addition to help understanding the disease. There is an increasing number of studies that propose to use deep learning to provide fast and accurate quantification of COVID-19 using che... | 214 | COVID-19;Disease Progression | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | Segmentation-only | CT |
34650825 | null | Yes | PMC8513790 | 34,650,825 | 2,021 | 2021-10-16 | Journal Article | Peer reviewed (PubMed) | 1 | context matters: graph-based self-supervised representation learning for medical images | Supervised learning method requires a large volume of annotated datasets. Collecting such datasets is time-consuming and expensive. Until now, very few annotated COVID-19 imaging datasets are available. Although self-supervised learning enables us to bootstrap the training by exploiting unlabeled data, the generic self... | 214 | COVID-19;Clinical Course | 2 | Proc Conf AAAI Artif Intell | Other Topics | 0.000001 | 4.2 | 0.000001 | 9 | 0 | External | 3. Monitoring/Severity assessment | CT |
33044938 | 10.1109/JBHI.2020.3030224 | Yes | null | 33,044,938 | 2,020 | 2020-10-13 | Journal Article;Research Support, N.I.H., Extramural | Peer reviewed (PubMed) | 1 | severity and consolidation quantification of covid-19 from ct images using deep learning based on hybrid weak labels | Early and accurate diagnosis of Coronavirus disease (COVID-19) is essential for patient isolation and contact tracing so that the spread of infection can be limited. Computed tomography (CT) can provide important information in COVID-19, especially for patients with moderate to severe disease as well as those with wors... | 214 | COVID-19;Infections;Pneumonia | 15 | IEEE J Biomed Health Inform | Severity of Illness Index;Coronavirus Infections;Algorithms;Iran;Semantics;Report;Retrospective Studies | 0.000003 | 38.944 | 0.000003 | 114 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
2007.12525 | 10.3390/make2040027 | Yes | null | null | 2,020 | 2020-07-24 | Preprint | arXiv | 0 | study of different deep learning approach with explainable ai for screening patients with covid-19 symptoms: using ct scan and chest x-ray image dataset | The outbreak of COVID-19 disease caused more than 100,000 deaths so far in the USA alone. It is necessary to conduct an initial screening of patients with the symptoms of COVID-19 disease to control the spread of the disease. However, it is becoming laborious to conduct the tests with the available testing kits due to ... | 214 | COVID-19;Death | null | null | Disease Outbreaks;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | Multimodal |
32588200 | 10.1007/s13246-020-00888-x | Yes | PMC7315909 | 32,588,200 | 2,020 | 2020-06-27 | Journal Article | Peer reviewed (PubMed) | 1 | truncated inception net: covid-19 outbreak screening using chest x-rays | Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a short period of time, and the infection, caused by SARS-CoV-2, is spreading rapidly. AI-driven tools are used to identify Coronavirus outbreaks as well as forecast their nature of spread, where imaging techniques are wid... | 214 | COVID-19;COVID-19 Pandemic;Infections;Pneumonia;Tuberculosis | 104 | Phys Eng Sci Med | Coronavirus Infections;Disease Outbreaks;Neural Networks;ROC Curve;Lung Diseases;Area under Curve | 0.000004 | 88.792 | 0.000006 | 255 | 0 | External | 2. Detection/Diagnosis | X-Ray |
34891687 | 10.1109/EMBC46164.2021.9630945 | Yes | null | 34,891,687 | 2,021 | 2021-12-12 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | interpreting uncertainty in model predictions for covid-19 diagnosis | COVID-19, due to its accelerated spread has brought in the need to use assistive tools for faster diagnosis in addition to typical lab swab testing. Chest X-Rays for COVID cases tend to show changes in the lungs such as ground glass opacities and peripheral consolidations which can be detected by deep neural networks. ... | 214 | COVID-19 | 0 | Annu Int Conf IEEE Eng Med Biol Soc | COVID-19 Testing;Other Topics | 0.000001 | 14.2 | 0.000001 | 37 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2004.04582 | null | Yes | null | null | 2,020 | 2020-06-06 | Preprint | arXiv | 0 | deepcovidexplainer: explainable covid-19 diagnosis based on chest x-ray images | Amid the coronavirus disease (COVID-19) pandemic, humanity experiences a rapid increase in infection numbers across the world. Challenge hospitals are faced with, in the fight against the virus, is the effective screening of incoming patients. One methodology is the assessment of chest radiography (CXR) images, which u... | 214 | COVID-19;COVID-19 Pandemic;Infections;Pneumonia | null | null | Coronavirus Infections;Map | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
35110593 | 10.1038/s41598-022-05532-0 | Yes | PMC8810911 | 35,110,593 | 2,022 | 2022-02-04 | Journal Article;Research Support, N.I.H., Extramural;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | effective deep learning approaches for predicting covid-19 outcomes from chest computed tomography volumes | The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence approaches to these problems, including using deep learning to predict COVI... | 215 | COVID-19;COVID-19 Pandemic;Pneumonia;Pneumonia, Viral | 6 | Sci Rep | Image Processing;Lung Diseases;Area under Curve;Map;Cone-Beam Computed Tomography | 0.000001 | 22.6 | 0.000002 | 37 | 0 | External | 4. Prognosis/Treatment | CT |
2004.06689 | null | Yes | null | null | 2,020 | 2020-04-14 | Preprint | arXiv | 0 | weakly supervised deep learning for covid-19 infection detection and classification from ct images | An outbreak of a novel coronavirus disease (i.e., COVID-19) has been recorded in Wuhan, China since late December 2019, which subsequently became pandemic around the world. Although COVID-19 is an acutely treated disease, it can also be fatal with a risk of fatality of 4.03% in China and the highest of 13.04% in Algeri... | 215 | COVID-19;Death;Infections;Respiratory Failure | null | null | Coronavirus Infections;Disease Outbreaks;Polymerase Chain Reaction;Reverse Transcription | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32408222 | 10.1016/j.ejrad.2020.109041 | Yes | PMC7198437 | 32,408,222 | 2,020 | 2020-05-15 | Journal Article;Multicenter Study | Peer reviewed (PubMed) | 1 | deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: a multicentre study | To develop a deep learning-based method to assist radiologists to fast and accurately identify patients with COVID-19 by CT images. We retrospectively collected chest CT images of 495 patients from three hospitals in China. 495 datasets were randomly divided into 395 cases (80%, 294 of COVID-19, 101 of other pneumonia)... | 216 | COVID-19;Pneumonia | 100 | Eur J Radiol | Coronavirus Infections;Radiologists;ROC Curve;Retrospective Studies;Age;Receiver Operating Characteristic | 0.000007 | 162.816 | 0.000009 | 440 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
32427226 | 10.1016/j.chemolab.2020.104054 | Yes | PMC7233238 | 32,427,226 | 2,020 | 2020-05-20 | Journal Article | Peer reviewed (PubMed) | 1 | an automated residual exemplar local binary pattern and iterative relieff based covid-19 detection method using chest x-ray image | Coronavirus is normally transmitted from animal to person, but nowadays it is transmitted from person to person by changing its form. Covid-19 appeared as a very dangerous virus and unfortunately caused a worldwide pandemic disease. Radiology doctors use X-ray or CT images for the diagnosis of Covid-19. It has become c... | 216 | COVID-19 | 65 | Chemometr Intell Lab Syst | Viruses;Decision Trees | 0.000003 | 46.696 | 0.000004 | 111 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2006.16106 | 10.1109/ICMLA51294.2020.00211 | Yes | null | null | 2,020 | 2020-10-20 | Preprint | arXiv | 0 | covid-19 screening using residual attention network an artificial intelligence approach | Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). The virus transmits rapidly; it has a basic reproductive number R of 2.2-2.7. In March 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. COVID-19 is currently affecting more ... | 216 | COVID-19;COVID-19 Pandemic;Severe Acute Respiratory Syndrome | null | null | World Health Organization;Disease Outbreaks;Health;Polymerase Chain Reaction;Map;Reverse Transcription | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33810066 | 10.3390/s21062215 | Yes | PMC8004971 | 33,810,066 | 2,021 | 2021-04-04 | Journal Article | Peer reviewed (PubMed) | 1 | a few-shot u-net deep learning model for covid-19 infected area segmentation in ct images | Recent studies indicate that detecting radiographic patterns on CT chest scans can yield high sensitivity and specificity for COVID-19 identification. In this paper, we scrutinize the effectiveness of deep learning models for semantic segmentation of pneumonia-infected area segmentation in CT images for the detection o... | 217 | COVID-19;Pneumonia | 38 | Sensors (Basel) | Semantics;Sensitivity and Specificity | 0.000002 | 46.28 | 0.000003 | 99 | 0 | External | Segmentation-only | CT |
32730216 | 10.1109/TMI.2020.2995108 | Yes | PMC7393217 | 32,730,216 | 2,020 | 2020-07-31 | Journal Article;Research Support, N.I.H., Extramural | Peer reviewed (PubMed) | 1 | relational modeling for robust and efficient pulmonary lobe segmentation in ct scans | Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pulmonary diseases. Recent works based on convolution neural networks have achieved good performance for this task. However, they are still limited in capturing structured relationships due to the nature of convolution. The... | 217 | COVID-19;Infections;Lung Diseases;Pulmonary Disease, Chronic Obstructive | 45 | IEEE Trans Med Imaging | Coronavirus Infections;Transfer Learning;Algorithms;Lung;Neural Networks;Tomography | 0.000002 | 29.344 | 0.000002 | 90 | 0 | Self-recorded/clinical | Segmentation-only | CT |
10.1101/2020.05.26.20113761 | 10.1101/2020.05.26.20113761 | Yes | null | null | 2,020 | 2020-05-27 | Preprint | medRxiv | 0 | differentiating covid-19 from other types of pneumonia with convolutional neural networks | A widely-used method for diagnosing COVID-19 is the nucleic acid test based on real-time reverse transcriptase-polymerase chain reaction (RT-PCR). However, the sensitivity of real time RT-PCR tests is low and it can take up to 8 hours to receive the test results. Radiologic methods can provide higher sensitivity. The a... | 217 | COVID-19;Pneumonia;Pneumonia, Bacterial;Pneumonia, Viral | null | null | Polymerase Chain Reaction;Area under Curve;Nucleic Acids | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
2009.09725 | null | Yes | null | null | 2,020 | 2020-09-21 | Preprint | arXiv | 0 | improving automated covid-19 grading with convolutional neural networks in computed tomography scans: an ablation study | Amidst the ongoing pandemic, several studies have shown that COVID-19 classification and grading using computed tomography (CT) images can be automated with convolutional neural networks (CNNs). Many of these studies focused on reporting initial results of algorithms that were assembled from commonly used components. T... | 218 | COVID-19 | null | null | Transfer Learning;Algorithms;Tomography;ROC Curve;Area under Curve;Map;Cone-Beam Computed Tomography | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | Multimodal |
10.1101/2020.08.13.20173997 | 10.1101/2020.08.13.20173997 | Yes | null | null | 2,020 | 2020-08-14 | Preprint | medRxiv | 0 | deep learning for automated recognition of covid-19 from chest x-ray images | The pandemic caused by coronavirus in recent months is having a devastating global effect, which puts the world under the most ever unprecedented emergency. Currently, since there are not effective antiviral treatments for Covid-19 yet, it is crucial to early detect and monitor the progression of the disease, thus help... | 218 | COVID-19 | null | null | Transfer Learning;Antiviral Agents;Pharmaceutical Preparations | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
34853342 | 10.1038/s41598-021-02003-w | Yes | PMC8636645 | 34,853,342 | 2,021 | 2021-12-03 | Journal Article;Research Support, Non-U.S. Gov't;Validation Study | Peer reviewed (PubMed) | 1 | validation of expert system enhanced deep learning algorithm for automated screening for covid-pneumonia on chest x-rays | SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based on X-Ray data. Here, addressing the lacunae in existing literature an... | 218 | COVID-19;Pneumonia | 3 | Sci Rep | Predictive Value;Image Processing;Polymerase Chain Reaction;Neural Networks;Radiologists;Retrospective Studies | 0.000002 | 77.84 | 0.000005 | 166 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
2006.14419 | null | Yes | null | null | 2,020 | 2020-06-26 | Preprint | arXiv | 0 | a novel and reliable deep learning web-based tool to detect covid-19 infection from chest ct-scan | The corona virus is already spread around the world in many countries, and it has taken many lives. Furthermore, the world health organization (WHO) has announced that COVID-19 has reached the global epidemic stage. Early and reliable diagnosis using chest CT-scan can assist medical specialists in vital circumstances. ... | 218 | COVID-19;Infections | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
34976571 | 10.1109/ACCESS.2021.3058537 | Yes | PMC8675557 | 34,976,571 | 2,022 | 2022-01-04 | Journal Article | Peer reviewed (PubMed) | 1 | a review on deep learning techniques for the diagnosis of novel coronavirus (covid-19) | Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world and has become one of the most acute and severe ailments in the past hundred years. The prevalence rate of COVID-19 is rapidly rising every day throughout the globe. Although no vaccines for this pandemic have been discovered ye... | 220 | COVID-19 | 93 | IEEE Access | Transfer Learning;Research Personnel;Disease Outbreaks;Tomography | 0.000002 | 48.2 | 0.000003 | 97 | 0 | N.A. | Review | Multimodal |
32787937 | 10.1186/s12938-020-00807-x | Yes | PMC7422684 | 32,787,937 | 2,020 | 2020-08-14 | Journal Article | Peer reviewed (PubMed) | 1 | rapid identification of covid-19 severity in ct scans through classification of deep features | Chest CT is used for the assessment of the severity of patients infected with novel coronavirus 2019 (COVID-19). We collected chest CT scans of 202 patients diagnosed with the COVID-19, and try to develop a rapid, accurate and automatic tool for severity screening follow-up therapeutic treatment. A total of 729 2D axia... | 220 | COVID-19 | 30 | Biomed Eng Online | Pneumonia;Decision Trees | 0.000003 | 56.56 | 0.000004 | 164 | 0 | External | 3. Monitoring/Severity assessment | CT |
34539221 | 10.1007/s11042-021-11299-9 | Yes | PMC8436200 | 34,539,221 | 2,021 | 2021-09-21 | Journal Article | Peer reviewed (PubMed) | 1 | automatic deep learning system for covid-19 infection quantification in chest ct | The paper proposes an automatic deep learning system for COVID-19 infection areas segmentation in chest CT scans. CT imaging proved its ability to detect the COVID-19 disease even for asymptotic patients, which make it a trustworthy alternative for PCR. Coronavirus disease spread globally and PCR screening is the adopt... | 221 | COVID-19;Infections;Postoperative Residual Curarization | 2 | Multimed Tools Appl | Coronavirus Infections;Polymerase Chain Reaction | 0.000001 | 21.24 | 0.000002 | 49 | 0 | External | Segmentation-only | CT |
32412551 | 10.1007/s40846-020-00529-4 | Yes | PMC7221329 | 32,412,551 | 2,020 | 2020-05-16 | Journal Article | Peer reviewed (PubMed) | 1 | extracting possibly representative covid-19 biomarkers from x-ray images with deep learning approach and image data related to pulmonary diseases | While the spread of COVID-19 is increased, new, automatic, and reliable methods for accurate detection are essential to reduce the exposure of the medical experts to the outbreak. X-ray imaging, although limited to specific visualizations, may be helpful for the diagnosis. In this study, the problem of automatic classi... | 222 | COVID-19;Lung Diseases | 126 | J Med Biol Eng | Art;Transfer Learning;Disease Outbreaks;Lung;Other Topics;Lung Diseases | 0.000003 | 72.264 | 0.000005 | 185 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2003.05037 | null | Yes | null | null | 2,020 | 2020-03-24 | Preprint | arXiv | 0 | rapid ai development cycle for the coronavirus (covid-19) pandemic: initial results for automated detection and patient monitoring using deep learning ct image analysis | Develop AI-based automated CT image analysis tools for detection, quantification, and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from non-patients. : Multiple international datasets, including from Chinese disease-infected areas were included. We present a system that utilizes robu... | 222 | COVID-19;COVID-19 Pandemic | null | null | Specificity;Area under Curve;Map | null | null | null | null | null | Self-recorded/clinical | 3. Monitoring/Severity assessment | CT |
33042210 | 10.1016/j.bspc.2020.102257 | Yes | PMC7538100 | 33,042,210 | 2,020 | 2020-10-13 | Journal Article | Peer reviewed (PubMed) | 1 | mh-covidnet: diagnosis of covid-19 using deep neural networks and meta-heuristic-based feature selection on x-ray images | COVID-19 is a disease that causes symptoms in the lungs and causes deaths around the world. Studies are ongoing for the diagnosis and treatment of this disease, which is defined as a pandemic. Early diagnosis of this disease is important for human life. This process is progressing rapidly with diagnostic studies based ... | 222 | COVID-19;Death;Pneumonia | 44 | Biomed Signal Process Control | Other Topics | 0.000003 | 29.664 | 0.000003 | 84 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32750973 | 10.1109/JBHI.2020.3012383 | Yes | PMC8545159 | 32,750,973 | 2,020 | 2020-08-06 | Journal Article;Research Support, Non-U.S. Gov't;Validation Study | Peer reviewed (PubMed) | 1 | introducing the gev activation function for highly unbalanced data to develop covid-19 diagnostic models | Fast and accurate diagnosis is essential for the efficient and effective control of the COVID-19 pandemic that is currently disrupting the whole world. Despite the prevalence of the COVID-19 outbreak, relatively few diagnostic images are openly available to develop automatic diagnosis algorithms. Traditional deep learn... | 222 | COVID-19;COVID-19 Pandemic;Pneumonia | 11 | IEEE J Biomed Health Inform | Coronavirus Infections;Disease Outbreaks;COVID-19 Testing;Neural Networks | 0.000003 | 36.184 | 0.000003 | 131 | 0 | External | 2. Detection/Diagnosis | Multimodal |
2008.09713 | null | Yes | null | null | 2,020 | 2020-08-21 | Preprint | arXiv | 0 | comparative performance analysis of the resnet backbones of mask rcnn to segment the signs of covid-19 in chest ct scans | COVID-19 has been detrimental in terms of the number of fatalities and rising number of critical patients across the world. According to the UNDP (United National Development Programme) Socio-Economic programme, aimed at the COVID-19 crisis, the pandemic is far more than a health crisis: it is affecting societies and e... | 222 | COVID-19 | null | null | Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | CT |
32989379 | 10.1016/j.asoc.2020.106744 | Yes | PMC7510455 | 32,989,379 | 2,020 | 2020-09-30 | Journal Article | Peer reviewed (PubMed) | 1 | learning distinctive filters for covid-19 detection from chest x-ray using shuffled residual cnn | COVID-19 is a deadly viral infection that has brought a significant threat to human lives. Automatic diagnosis of COVID-19 from medical imaging enables precise medication, helps to control community outbreak, and reinforces coronavirus testing methods in place. While there exist several challenges in manually inferring... | 222 | COVID-19;Pneumonia;Virus Diseases | 33 | Appl Soft Comput | Architecture;Disease Outbreaks | 0.000004 | 62.112 | 0.000005 | 164 | 0 | External | 2. Detection/Diagnosis | X-Ray |
34101042 | 10.1007/s10916-021-01745-4 | Yes | PMC8185498 | 34,101,042 | 2,021 | 2021-06-09 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning on chest x-ray images to detect and evaluate pneumonia cases at the era of covid-19 | Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world, causing then the 2019-20 coronavirus pandemic. In many cases, this disease causes pneumonia. Since pulmonary infections can be observed... | 223 | COVID-19;Communicable Diseases;Infections;Pneumonia;Pneumonia, Viral | 54 | J Med Syst | Coronavirus Infections;Architecture;Neural Networks;Communicable Diseases | 0.000003 | 165.92 | 0.000011 | 326 | 0 | External | 2. Detection/Diagnosis | X-Ray |
33199977 | 10.1016/j.asoc.2020.106897 | Yes | PMC7654325 | 33,199,977 | 2,020 | 2020-11-18 | Journal Article | Peer reviewed (PubMed) | 1 | ai-assisted ct imaging analysis for covid-19 screening: building and deploying a medical ai system | The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough ... | 223 | COVID-19;Infections;Lung Diseases;Pneumonia | 181 | Appl Soft Comput | Disease Outbreaks;Radiologists | 0.000005 | 94.712 | 0.000007 | 241 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
2009.05096 | null | Yes | null | null | 2,020 | 2020-09-10 | Preprint | arXiv | 0 | covid ct-net: predicting covid-19 from chest ct images using attentional convolutional network | The novel corona-virus disease (COVID-19) pandemic has caused a major outbreak in more than 200 countries around the world, leading to a severe impact on the health and life of many people globally. As of Aug 25th of 2020, more than 20 million people are infected, and more than 800,000 death are reported. Computed Tomo... | 224 | COVID-19;Death | null | null | Specificity;Research Personnel;Disease Outbreaks;Health;Polymerase Chain Reaction;Radiologists;Map;Reverse Transcription | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
2012.10787 | null | Yes | null | null | 2,021 | 2021-02-12 | Preprint | arXiv | 0 | constructing and evaluating an explainable model for covid-19 diagnosis from chest x-rays | In this paper, our focus is on constructing models to assist a clinician in the diagnosis of COVID-19 patients in situations where it is easier and cheaper to obtain X-ray data than to obtain high-quality images like those from CT scans. Deep neural networks have repeatedly been shown to be capable of constructing high... | 224 | COVID-19;Pneumonia | null | null | Pneumonia;Other Topics;Decision Trees;Map | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
34786295 | 10.1109/ACCESS.2020.3033762 | Yes | PMC8545263 | 34,786,295 | 2,021 | 2021-11-18 | Journal Article | Peer reviewed (PubMed) | 1 | deep convolutional approaches for the analysis of covid-19 using chest x-ray images from portable devices | The recent human coronavirus disease (COVID-19) is a respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the effects of COVID-19 in pulmonary tissues, chest radiography imaging plays an important role in the screening, early detection, and monitoring of the suspected indi... | 224 | COVID-19;Infections;Respiratory Tract Infections;Severe Acute Respiratory Syndrome | 24 | IEEE Access | Other Topics | 0.000003 | 34.4 | 0.000003 | 92 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | X-Ray |
32834634 | 10.1016/j.chaos.2020.110122 | Yes | PMC7357532 | 32,834,634 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | convolutional capsnet: a novel artificial neural network approach to detect covid-19 disease from x-ray images using capsule networks | Coronavirus is an epidemic that spreads very quickly. For this reason, it has very devastating effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as possible to restrain the spread of the disease. The similarity of COVID-19 disease with other lung infections makes the diagnosis difficul... | 225 | COVID-19;Infections;Pneumonia | 102 | Chaos Solitons Fractals | Other Topics | 0.000006 | 114.528 | 0.000008 | 284 | 0 | External | 2. Detection/Diagnosis | X-Ray |
32837591 | 10.1007/s12559-020-09751-3 | Yes | PMC7429098 | 32,837,591 | 2,020 | 2020-08-25 | Journal Article | Peer reviewed (PubMed) | 1 | social group optimization-assisted kapur's entropy and morphological segmentation for automated detection of covid-19 infection from computed tomography images | The coronavirus disease (COVID-19) caused by a novel coronavirus, SARS-CoV-2, has been declared a global pandemic. Due to its infection rate and severity, it has emerged as one of the major global threats of the current generation. To support the current combat against the disease, this research aims to propose a machi... | 225 | COVID-19;Infections | 35 | Cognit Comput | Entropy;Support Vector Machine;Decision Trees;Cluster Analysis;Random Forest | 0.000003 | 33.248 | 0.000003 | 82 | 0 | External | 2. Detection/Diagnosis | CT |
33169099 | 10.1016/j.scs.2020.102589 | Yes | PMC7642729 | 33,169,099 | 2,020 | 2020-11-11 | Journal Article | Peer reviewed (PubMed) | 1 | deep learning and medical image processing for coronavirus (covid-19) pandemic: a survey | Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many death cases and affected all sectors of human life. With gradual progression of time, COVID-19 was declared by the world health organization (WHO) as an outbreak, which has imposed a heavy burden on almost all countries, especially ones wi... | 225 | COVID-19;COVID-19 Pandemic;Death;Diabetic Retinopathy | 126 | Sustain Cities Soc | Art;World Health Organization;Health Care;Disease Outbreaks;Image Processing;Tomography;Lung Diseases | 0.000008 | 101.952 | 0.000007 | 266 | 0 | N.A. | Review | Multimodal |
10.1101/2020.08.03.20167007 | 10.1101/2020.08.03.20167007 | Yes | null | null | 2,020 | 2020-08-04 | Preprint | medRxiv | 0 | severity assessment and progression prediction of covid-19 patients based on the lesionencoder framework and chest ct | Automatic severity assessment and progression prediction can facilitate admission, triage, and referral of COVID-19 patients. This study aims to explore the potential use of lung lesion features in the management of COVID-19, based on the assumption that lesion features may carry important diagnostic and prognostic inf... | 225 | COVID-19;Disease Progression;Infections | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 4. Prognosis/Treatment | CT |
32915751 | 10.1109/JBHI.2020.3023246 | Yes | null | 32,915,751 | 2,020 | 2020-09-12 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | contrastive cross-site learning with redesigned net for covid-19 ct classification | The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health crisis spreading hundreds of countries. With the continuous growth of new infections, developing automated tools for COVID-19 identification with CT image is highly desired to assist the clinical diagnosis and reduce the tedious work... | 226 | COVID-19;Infections | 72 | IEEE J Biomed Health Inform | Coronavirus Infections;Public Health;Art;Pandemics;Architecture;COVID-19 Testing;Semantics;Health;Tomography;Paper;Area under Curve;Tests | 0.000006 | 132.32 | 0.000007 | 370 | 0 | External | 2. Detection/Diagnosis | CT |
2011.14894 | null | Yes | null | null | 2,020 | 2020-11-27 | Preprint | arXiv | 0 | uncertainty-driven ensembles of deep architectures for multiclass classification application to covid-19 diagnosis in chest x-ray images | Respiratory diseases kill million of people each year. Diagnosis of these pathologies is a manual, time-consuming process that has inter and intra-observer variability, delaying diagnosis and treatment. The recent COVID-19 pandemic has demonstrated the need of developing systems to automatize the diagnosis of pneumonia... | 227 | COVID-19;COVID-19 Pandemic;Pneumonia;Pneumonia, Bacterial;Pneumonia, Viral | null | null | Pneumonia;Decision Trees | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
32444412 | 10.1183/13993003.00775-2020 | Yes | PMC7243395 | 32,444,412 | 2,020 | 2020-05-24 | Journal Article | Peer reviewed (PubMed) | 1 | a fully automatic deep learning system for covid-19 diagnostic and prognostic analysis | Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with worse prognosis for early prevention and medical resource optimisation is important. Here, we proposed a fully automatic deep learning system... | 228 | COVID-19;Pneumonia;Pneumonia, Viral | 214 | Eur Respir J | Coronavirus Infections;Retrospective Studies | 0.000006 | 137.624 | 0.000008 | 371 | 0 | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33170789 | 10.1109/JBHI.2020.3037127 | Yes | null | 33,170,789 | 2,020 | 2020-11-11 | Journal Article;Research Support, Non-U.S. Gov't | Peer reviewed (PubMed) | 1 | covidgr dataset and covid-sdnet methodology for predicting covid-19 based on chest x-ray images | Currently, Coronavirus disease (COVID-19), one of the most infectious diseases in the 21st century, is diagnosed using RT-PCR testing, CT scans and/or Chest X-Ray (CXR) images. CT (Computed Tomography) scanners and RT-PCR testing are not available in most medical centers and hence in many cases CXR images become the mo... | 228 | COVID-19;Communicable Diseases | 84 | IEEE J Biomed Health Inform | Polymerase Chain Reaction;Communicable Diseases | 0.000003 | 48.952 | 0.000004 | 125 | 0 | Self-recorded/clinical | 3. Monitoring/Severity assessment | X-Ray |
10.1101/2020.05.25.20113084 | 10.1101/2020.05.25.20113084 | Yes | null | null | 2,020 | 2020-05-27 | Preprint | medRxiv | 0 | a chest radiography-based artificial intelligence deep-learning model to predict severe covid-19 patient outcomes: the cape (covid-19 ai predictive engine) model | Chest radiography may be used together with deep-learning models to prognosticate COVID-19 patient outcomesT o evaluate the performance of a deep-learning model for the prediction of severe patient outcomes from COVID-19 pneumonia on chest radiographs.A deep-learning model (CAPE: Covid-19 AI Predictive Engine) was trai... | 229 | COVID-19;Pneumonia | null | null | Polymerase Chain Reaction;Area under Curve | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.03.28.20046045 | 10.1101/2020.03.28.20046045 | Yes | null | null | 2,020 | 2020-03-30 | Preprint | medRxiv | 0 | deep learning-based recognizing covid-19 and other common infectious diseases of the lung by chest ct scan images | COVID-19 has become global threaten. CT acts as an important method of diagnosis. However, human-based interpretation of CT imaging is time consuming. More than that, substantial inter-observer-variation cannot be ignored. We aim at developing a diagnostic tool for artificial intelligence (AI)-based classification of C... | 229 | COVID-19;Communicable Diseases;Pneumonia;Pneumonia, Bacterial;Pneumonia, Viral;Tuberculosis, Pulmonary | null | null | Other Topics | null | null | null | null | null | Self-recorded/clinical | 2. Detection/Diagnosis | CT |
33824721 | 10.1007/s13755-021-00146-8 | Yes | PMC8015934 | 33,824,721 | 2,021 | 2021-04-08 | Journal Article | Peer reviewed (PubMed) | 1 | covid-19 infection map generation and detection from chest x-ray images | Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep Learning techniques for COVID-19 diagnosis. However, they have used very limited chest X-ray (CXR) ima... | 229 | COVID-19;Infections | 29 | Health Inf Sci Syst | Art;Specificity;Masks;Map | 0.000001 | 30.4 | 0.000002 | 66 | 0 | External | 2. Detection/Diagnosis | X-Ray |
2011.14983 | null | Yes | null | null | 2,021 | 2021-02-02 | Preprint | arXiv | 0 | mavidh score: a covid-19 severity scoring using chest x-ray pathology features | The application of computer vision for COVID-19 diagnosis is complex and challenging, given the risks associated with patient misclassifications. Arguably, the primary value of medical imaging for COVID-19 lies rather on patient prognosis. Radiological images can guide physicians assessing the severity of the disease, ... | 230 | COVID-19;Disease Progression | null | null | Other Topics | null | null | null | null | null | External | 3. Monitoring/Severity assessment | X-Ray |
2004.10507 | null | Yes | null | null | 2,020 | 2020-08-21 | Preprint | arXiv | 0 | deep learning for screening covid-19 using chest x-ray images | With the ever increasing demand for screening millions of prospective "novel coronavirus" or COVID-19 cases, and due to the emergence of high false negatives in the commonly used PCR tests, the necessity for probing an alternative simple screening mechanism of COVID-19 using radiological images (like chest X-Rays) assu... | 230 | COVID-19;Pneumonia | null | null | Transfer Learning;Lung;Polymerase Chain Reaction;Other Topics;Lung Diseases;Map | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
10.1101/2020.07.15.20154385 | 10.1101/2020.07.15.20154385 | Yes | null | null | 2,020 | 2020-07-16 | Preprint | medRxiv | 0 | interpreting deep ensemble learning through radiologist annotations 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, using these models in medical computer vision tasks suffers from several limitations, viz., adapting to visual characteristics that are unlike natural imag... | 230 | COVID-19 | null | null | Black Americans;Noise;X-Rays;Radiologists;Other Topics | null | null | null | null | null | External | 2. Detection/Diagnosis | X-Ray |
33061946 | 10.1155/2020/8889023 | Yes | PMC7539085 | 33,061,946 | 2,020 | 2020-10-17 | Journal Article | Peer reviewed (PubMed) | 1 | artificial intelligence-based classification of chest x-ray images into covid-19 and other infectious diseases | The ongoing pandemic of coronavirus disease 2019 (COVID-19) has led to global health and healthcare crisis, apart from the tremendous socioeconomic effects. One of the significant challenges in this crisis is to identify and monitor the COVID-19 patients quickly and efficiently to facilitate timely decisions for their ... | 231 | COVID-19;Communicable Diseases;Pneumonia;Tuberculosis | 34 | Int J Biomed Imaging | Health Care;Transfer Learning;Polymerase Chain Reaction;Communicable Diseases | 0.000003 | 40.72 | 0.000003 | 108 | 0 | External | 2. Detection/Diagnosis | X-Ray |
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