An increasing number of convolutional neural networks for fracture recognition and classification in orthopaedics: are these externally validated and ready for clinical application?

An increasing number of convolutional neural networks for fracture recognition and classification in orthopaedics: are these externally validated and ready for clinical application?

Aims: The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizabilit...

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Bibliographic Details
Main Authors: Luisa Oliveira e Carmo, Anke van den Merkhof, Jakub Olczak, Max Gordon, Paul C. Jutte, Ruurd L. Jaarsma, Frank F. A. IJpma, Job N. Doornberg, Jasper Prijs, Machine Learning Consortium
Format: Article
Language:English
Published: The British Editorial Society of Bone & Joint Surgery 2021-10-01
Series:Bone & Joint Open
Subjects:
artificial intelligence
external validation
convolutional neural networks
machine learning
deep learning
orthopaedic trauma
prognosis
radiographs
orthopaedic surgeons
elbows
ct scans
hip
distal radius fractures
variances
cadaveric studies
Online Access:https://online.boneandjoint.org.uk/doi/epdf/10.1302/2633-1462.210.BJO-2021-0133

Internet

https://online.boneandjoint.org.uk/doi/epdf/10.1302/2633-1462.210.BJO-2021-0133

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