Artificial intelligence in traumatology.
Journal
Bone & joint research
ISSN: 2046-3758
Titre abrégé: Bone Joint Res
Pays: England
ID NLM: 101586057
Informations de publication
Date de publication:
17 Oct 2024
17 Oct 2024
Historique:
medline:
17
10
2024
pubmed:
17
10
2024
entrez:
17
10
2024
Statut:
epublish
Résumé
The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared. At the time of the study, the CNN model showed an area under the receiver operating curve of 0.97. AI assistance improved the physician's sensitivity (correct fracture detection) from 80% to 87%, and the specificity (correct fracture exclusion) from 91% to 95%. The overall error rate (combined false positive and false negative) was reduced from 14% without AI to 9% with AI. The use of a CNN model as a second opinion can improve the diagnostic accuracy of DRF detection in the study setting.
Identifiants
pubmed: 39417424
doi: 10.1302/2046-3758.1310.BJR-2023-0275.R3
pii: BJR-2023-0275.R3
doi:
Types de publication
Journal Article
Langues
eng
Pagination
588-595Subventions
Organisme : Wirtschaftsagentur Wien
Informations de copyright
© 2024 Breu et al.
Déclaration de conflit d'intérêts
C. Avelar, Z. Bertalan, and R. Ljuhar are employees of ImageBiopsy Lab. All other authors and the readers declare no conflict of interest.
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