Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs.
AuthorJones, Rebecca M
Sperling, John W
Roberts, Matthew M
Potter, Hollis G
Lindsey, Robert V
JournalNPJ Digital Medicine
MetadataShow full item record
AbstractMissed 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 itemhttp://hdl.handle.net/10713/14053
- Deep neural network improves fracture detection by clinicians.
- Authors: Lindsey R, Daluiski A, Chopra S, Lachapelle A, Mozer M, Sicular S, Hanel D, Gardner M, Gupta A, Hotchkiss R, Potter H
- Issue date: 2018 Nov 6
- Deep learning for the radiographic diagnosis of proximal femur fractures: Limitations and programming issues.
- Authors: Guy S, Jacquet C, Tsenkoff D, Argenson JN, Ollivier M
- Issue date: 2021 Apr
- Fractures of the fingers missed or misdiagnosed on poorly positioned or poorly taken radiographs: a retrospective study.
- Authors: Tuncer S, Aksu N, Dilek H, Ozkan T, Hamzaoglu A
- Issue date: 2011 Sep
- Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?
- Authors: Langerhuizen DWG, Bulstra AEJ, Janssen SJ, Ring D, Kerkhoffs GMMJ, Jaarsma RL, Doornberg JN
- Issue date: 2020 Nov
- Traumatic fractures in adults: missed diagnosis on plain radiographs in the Emergency Department.
- Authors: Pinto A, Berritto D, Russo A, Riccitiello F, Caruso M, Belfiore MP, Papapietro VR, Carotti M, Pinto F, Giovagnoni A, Romano L, Grassi R
- Issue date: 2018 Jan 19