Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs Using Convolutional Siamese Neural Networks-Reference-Cited by-同舟云学术

Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs Using Convolutional Siamese Neural Networks

Published:2020-07-01 Issue:4 Volume:2 Page:e200079
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Li Matthew D.^ORCID,Arun Nishanth T.,Gidwani Mishka^ORCID,Chang Ken^ORCID,Deng Francis^ORCID,Little Brent P.^ORCID,Mendoza Dexter P.^ORCID,Lang Min^ORCID,Lee Susanna I.^ORCID,O’Shea Aileen^ORCID,Parakh Anushri^ORCID,Singh Praveer^ORCID,Kalpathy-Cramer Jayashree^ORCID

Funder

National Institute of Biomedical Imaging and Bioengineering

National Cancer Institute

National Institutes of Health

Center for Functional Neuroimaging Technologies

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.2020200079

Reference21 articles.

1. ACR Recommendations for the Use of Chest Radiography and Computed Tomography (CT) for Suspected COVID-19 Infection. American College of Radiology. https://www.acr.org/Advocacy-and-Economics/ACR-Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection. Accessed March 27, 2020.

2. The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society

3. Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19

4. Interobserver Reliability of the Chest Radiograph in Community-Acquired Pneumonia

5. Interobserver Reliability of Radiologists’ Interpretations of Mobile Chest Radiographs for Nursing Home–Acquired Pneumonia

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