Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation

Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation

Summary: Background: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for ARDS. We sought to train a deep convolu...

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Bibliographic Details
Main Authors: Michael W Sjoding, MD, Daniel Taylor, MS, Jonathan Motyka, MS, Elizabeth Lee, MD, Ivan Co, MD, Dru Claar, MD, Jakob I McSparron, MD, Sardar Ansari, PhD, Meeta Prasad Kerlin, MD, John P Reilly, MD, Michael G S Shashaty, MD, Brian J Anderson, MD, Tiffanie K Jones, MD, Harrison M Drebin, MD, Caroline A G Ittner, MD, Nuala J Meyer, MD, Theodore J Iwashyna, ProfMD, Kevin R Ward, ProfMD, Christopher E Gillies, PhD
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:The Lancet: Digital Health
Online Access:http://www.sciencedirect.com/science/article/pii/S258975002100056X

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http://www.sciencedirect.com/science/article/pii/S258975002100056X

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