Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs.
Author
Jones, Rebecca MSharma, Anuj
Hotchkiss, Robert
Sperling, John W
Hamburger, Jackson
Ledig, Christian
O'Toole, Robert
Gardner, Michael
Venkatesh, Srivas
Roberts, Matthew M
Sauvestre, Romain
Shatkhin, Max
Gupta, Anant
Chopra, Sumit
Kumaravel, Manickam
Daluiski, Aaron
Plogger, Will
Nascone, Jason
Potter, Hollis G
Lindsey, Robert V
Date
2020-10-30Journal
NPJ Digital MedicinePublisher
Springer NatureType
Article
Metadata
Show full item recordAbstract
Missed fractures are the most common diagnostic error in emergency departments and can lead to treatment delays and long-term disability. Here we show through a multi-site study that a deep-learning system can accurately identify fractures throughout the adult musculoskeletal system. This approach may have the potential to reduce future diagnostic errors in radiograph interpretation.Rights/Terms
© The Author(s) 2020.Identifier to cite or link to this item
http://hdl.handle.net/10713/14053ae974a485f413a2113503eed53cd6c53
10.1038/s41746-020-00352-w
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