Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19

Abstract Chest radiography (CXR) is the most widely-used thoracic clinical imaging modality and is crucial for guiding the management of cardiothoracic conditions. The detection of specific CXR findings has been the main focus of several artificial intelligence (AI) systems. However, the wide range...

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Auteurs principaux:	Zaid Nabulsi, Andrew Sellergren, Shahar Jamshy, Charles Lau, Edward Santos, Atilla P. Kiraly, Wenxing Ye, Jie Yang, Rory Pilgrim, Sahar Kazemzadeh, Jin Yu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Florencia Garcia-Vicente, David Melnick, Greg S. Corrado, Lily Peng, Krish Eswaran, Daniel Tse, Neeral Beladia, Yun Liu, Po-Hsuan Cameron Chen, Shravya Shetty
Format:	article
Langue:	EN
Publié:	Nature Portfolio 2021
Sujets:	Medicine R Science Q
Accès en ligne:	https://doaj.org/article/31c65be9be1043d9a386af4cf67b5c5c
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Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19

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