Effectiveness of COVID-19 diagnosis and management tools: A review

[1]  N. Paul,et al.  Radiologic pattern of disease in patients with severe acute respiratory syndrome: the Toronto experience. , 2004, Radiographics : a review publication of the Radiological Society of North America, Inc.

[2]  T. Franquet.  Imaging of pulmonary viral pneumonia. , 2011, Radiology.

[3]  Sameer Antani,et al.  Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs , 2018, Applied sciences.

[4]  Daniel S. Kermany,et al.  Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning , 2018, Cell.

[5]  Jaron J. R. Chong,et al.  Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology , 2018, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

[6]  Ahmed Hosny,et al.  Artificial intelligence in radiology , 2018, Nature Reviews Cancer.

[7]  S. Buck.  Corrigendum: The ‘upside down’: exploring offset pricing models and article deposit terms at King Abdullah University of Science and Technology (KAUST) , 2018 .

[8]  James H Thrall,et al.  Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success. , 2018, Journal of the American College of Radiology : JACR.

[9]  G. Corrado,et al.  End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography , 2019, Nature Medicine.

[10]  Hayit Greenspan,et al.  Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis , 2020, ArXiv.

[11]  Hannah R. Meredith,et al.  The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application , 2020, Annals of Internal Medicine.

[12]  Yan Zhao,et al.  Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. , 2020, JAMA.

[13]  Wim Naudé,et al.  Artificial Intelligence Against Covid-19: An Early Review , 2020, SSRN Electronic Journal.

[14]  C. Zheng,et al.  Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19) , 2020 .

[15]  Z. Memish,et al.  The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health — The latest 2019 novel coronavirus outbreak in Wuhan, China , 2020, International Journal of Infectious Diseases.

[16]  F. Shan,et al.  Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia , 2020, Radiology.

[17]  K. Cao,et al.  Artificial Intelligence Distinguishes COVID-19 from Community Acquired Pneumonia on Chest CT , 2020, Radiology.

[18]  S. Abbara,et al.  The Many Faces of COVID-19: Spectrum of Imaging Manifestations , 2020, Radiology. Cardiothoracic imaging.

[19]  J. Ioannidis,et al.  Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters , 2020, Environmental Research.

[20]  B. Song,et al.  Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review , 2020, European Radiology.

[21]  Jun Liu,et al.  Relation Between Chest CT Findings and Clinical Conditions of Coronavirus Disease (COVID-19) Pneumonia: A Multicenter Study. , 2020, AJR. American journal of roentgenology.

[22]  Alexandra Luccioni,et al.  Mapping the Landscape of Artificial Intelligence Applications against COVID-19 , 2020, J. Artif. Intell. Res..

[23]  S. Balakrishnan,et al.  Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. , 2020, AJR. American journal of roentgenology.

[24]  Kun Chen,et al.  Characteristics of COVID-19 infection in Beijing , 2020, Journal of Infection.

[25]  J. LeBlanc,et al.  A combined oropharyngeal/nares swab is a suitable alternative to nasopharyngeal swabs for the detection of SARS-CoV-2 , 2020, Journal of Clinical Virology.

[26]  Xin Wang,et al.  Learning tree-structured representation for 3D coronary artery segmentation , 2019, Comput. Medical Imaging Graph..

[27]  Ying Zhu,et al.  Clinical and CT imaging features of 2019 novel coronavirus disease (COVID-19) , 2020, Journal of Infection.

[28]  Bo Xu,et al.  A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19) , 2020, European Radiology.

[29]  Liming Cheng,et al.  Comparison of nasopharyngeal and oropharyngeal swabs for SARS-CoV-2 detection in 353 patients received tests with both specimens simultaneously , 2020, International Journal of Infectious Diseases.

[30]  Thanh Thi Nguyen,et al.  Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions , 2020, ArXiv.

[31]  P. Khong,et al.  COVID-19 pneumonia: what has CT taught us? , 2020, The Lancet Infectious Diseases.

[32]  G. Tonon,et al.  Why is chest CT important for early diagnosis of COVID-19? Prevalence matters , 2020, medRxiv.

[33]  Chuanming Li,et al.  The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia , 2020, Investigative radiology.

[34]  L. Xia,et al.  Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. , 2020, AJR. American journal of roentgenology.

[35]  T. Egglin,et al.  Performance of radiologists in differentiating COVID-19 from viral pneumonia on chest CT , 2020, Radiology.

[36]  Huixia Yang,et al.  Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records , 2020, The Lancet.

[37]  Q. Pham,et al.  Importation and Human-to-Human Transmission of a Novel Coronavirus in Vietnam , 2020, The New England journal of medicine.

[38]  R. Armitage,et al.  COVID-19 and the consequences of isolating the elderly , 2020, The Lancet Public Health.

[39]  R. Gandhi.  Clinical Characteristics of 2019 Novel Coronavirus Infection , 2020 .

[40]  Jun Liu,et al.  Chest CT for Typical 2019-nCoV Pneumonia: Relationship to Negative RT-PCR Testing , 2020, Radiology.

[41]  Q. Tao,et al.  Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases , 2020, Radiology.

[42]  Yi Yang,et al.  Lower mortality of COVID-19 by early recognition and intervention: experience from Jiangsu Province , 2020, Annals of Intensive Care.

[43]  Wenyu Liu,et al.  Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label , 2020, medRxiv.

[44]  Philip H. S. Torr,et al.  Deep learning for predicting COVID-19 malignant progression , 2020, Medical Image Analysis.

[45]  Hayit Greenspan,et al.  Coronavirus Detection and Analysis on Chest CT with Deep Learning , 2020, ArXiv.

[46]  Jay K Pahade,et al.  Utility of Artificial Intelligence Tool as a Prospective Radiology Peer Reviewer - Detection of Unreported Intracranial Hemorrhage. , 2020, Academic radiology.

[47]  L. Xia,et al.  Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China , 2020, European Radiology.

[48]  K. Yuen,et al.  Imaging Profile of the COVID-19 Infection: Radiologic Findings and Literature Review , 2020, Radiology. Cardiothoracic imaging.

[49]  Yu Zhou,et al.  Predicting COVID-19 malignant progression with AI techniques , 2020, medRxiv.

[50]  Lei Liu,et al.  Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections , 2020, medRxiv.

[51]  D. Rajgor,et al.  The many estimates of the COVID-19 case fatality rate , 2020, The Lancet Infectious Diseases.

[52]  Charmaine Butt,et al.  Deep learning system to screen coronavirus disease 2019 pneumonia , 2020, Applied Intelligence.

[53]  Q. Tao,et al.  Serial Quantitative Chest CT Assessment of COVID-19: A Deep Learning Approach , 2020, Radiology. Cardiothoracic imaging.

[54]  A. Laghi,et al.  Chest CT Features of COVID-19 in Rome, Italy , 2020, Radiology.

[55]  Hui Dai,et al.  High-resolution Chest CT Features and Clinical Characteristics of Patients Infected with COVID-19 in Jiangsu, China , 2020, International Journal of Infectious Diseases.

[56]  T. Singhal.  A Review of Coronavirus Disease-2019 (COVID-19) , 2020, The Indian Journal of Pediatrics.

[57]  Long Jiang Zhang,et al.  Coronavirus Disease 2019 (COVID-19): A Perspective from China , 2020, Radiology.

[58]  Fan Lin,et al.  CT Imaging and Differential Diagnosis of COVID-19 , 2020, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

[59]  W. Liang,et al.  Clinical characteristics of 2019 novel coronavirus infection in China , 2020, medRxiv.

[60]  Raymond Y Huang,et al.  AI Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Etiology on Chest CT , 2020, Radiology.

[61]  Wenjie Yang,et al.  Patients with RT-PCR-confirmed COVID-19 and Normal Chest CT , 2020, Radiology.

[62]  S. Scarlata,et al.  COVID‐19 diagnosis and management: a comprehensive review , 2020, Journal of internal medicine.

[63]  Z. Fayad,et al.  CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV) , 2020, Radiology.

[64]  J. Guarner.  Three Emerging Coronaviruses in Two Decades , 2020, American journal of clinical pathology.

[65]  Weidong Wu,et al.  Virology, Epidemiology, Pathogenesis, and Control of COVID-19 , 2020, Viruses.

[66]  Lian-lian Wu,et al.  Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study , 2020, medRxiv.

[67]  Wenjie Yang,et al.  Clinical characteristics and imaging manifestations of the 2019 novel coronavirus disease (COVID-19):A multi-center study in Wenzhou city, Zhejiang, China , 2020, Journal of Infection.

[68]  A. Kliger,et al.  Mitigating Risk of COVID-19 in Dialysis Facilities. , 2020, Clinical journal of the American Society of Nephrology : CJASN.

[69]  Development and Evaluation of an AI System for COVID-19 Diagnosis , 2020 .

[70]  J. Klausner,et al.  Self-Collected Oral Fluid and Nasal Swabs Demonstrate Comparable Sensitivity to Clinician Collected Nasopharyngeal Swabs for Covid-19 Detection , 2020, medRxiv.

[71]  Lo'ai Alanagreh,et al.  The Human Coronavirus Disease COVID-19: Its Origin, Characteristics, and Insights into Potential Drugs and Its Mechanisms , 2020, Pathogens.

[72]  T. Fan,et al.  CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China , 2020, Journal of Infection.

[73]  Jonathan H. Chung,et al.  Essentials for Radiologists on COVID-19: An Update—Radiology Scientific Expert Panel , 2020, Radiology.

[74]  S. Lei,et al.  Clinical characteristics and outcomes of patients undergoing surgeries during the incubation period of COVID-19 infection , 2020, EClinicalMedicine.

[75]  Mingzhi Li,et al.  Coronavirus Disease (COVID-19): Spectrum of CT Findings and Temporal Progression of the Disease , 2020, Academic Radiology.

[76]  D. Shen,et al.  Lung Infection Quantification of COVID-19 in CT Images with Deep Learning , 2020, ArXiv.

[77]  Yicheng Fang,et al.  Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR , 2020, Radiology.

[78]  W. Gardner,et al.  The Coronavirus and the Risks to the Elderly in Long-Term Care , 2020, Journal of aging & social policy.

[79]  Constantine A Raptis,et al.  Chest CT and Coronavirus Disease (COVID-19): A Critical Review of the Literature to Date. , 2020, AJR. American journal of roentgenology.

[80]  Heshui Shi,et al.  Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study , 2020, The Lancet Infectious Diseases.

[81]  K. Cao,et al.  Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy , 2020 .

[82]  Peikai Huang,et al.  Use of Chest CT in Combination with Negative RT-PCR Assay for the 2019 Novel Coronavirus but High Clinical Suspicion , 2020, Radiology.

[83]  W. Zeng,et al.  Chest CT Findings in Patients With Coronavirus Disease 2019 and Its Relationship With Clinical Features , 2020, Investigative radiology.

[84]  Dinggang Shen,et al.  Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19 , 2020, IEEE Reviews in Biomedical Engineering.

[85]  Kayhan Zrar Ghafoor,et al.  Diagnosing COVID-19 pneumonia from x-ray and CT images using deep learning and transfer learning algorithms , 2020, Defense + Commercial Sensing.