@article{59ef6ab8a26d46209374d3664d0732d9,
title = "Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs",
abstract = "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.",
author = "Jones, {Rebecca M.} and Anuj Sharma and Robert Hotchkiss and Sperling, {John W.} and Jackson Hamburger and Christian Ledig and Robert O{\textquoteright}Toole and Michael Gardner and Srivas Venkatesh and Roberts, {Matthew M.} and Romain Sauvestre and Max Shatkhin and Anant Gupta and Sumit Chopra and Manickam Kumaravel and Aaron Daluiski and Will Plogger and Jason Nascone and Potter, {Hollis G.} and Lindsey, {Robert V.}",
note = "Funding Information: The authors declare the following financial competing interest: financial support for the research was provided by Imagen Technologies, Inc. R.V.L., J.H., R.M.J., S.V., A.S., R.S., M.S., A.G., S.C., W.P., and C.L. are employees of Imagen Technologies, Inc. All authors are shareholders at Imagen Technologies, Inc. The authors declare that there are no non-financial competing interests. Publisher Copyright: {\textcopyright} 2020, The Author(s).",
year = "2020",
month = dec,
day = "1",
doi = "10.1038/s41746-020-00352-w",
language = "English (US)",
volume = "3",
journal = "npj Digital Medicine",
issn = "2398-6352",
publisher = "Nature Publishing Group",
number = "1",
}