AI for detection, classification and prediction of loss of alignment of distal radius fractures; a systematic review.

Purpose: Early and accurate assessment of distal radius fractures (DRFs) is crucial for optimal prognosis. Identifying fractures likely to lose threshold alignment (instability) in a cast is vital for treatment decisions, yet prediction tools' accuracy and reliability remain challenging. Artificial...

Descripción completa

Detalles Bibliográficos

Publicado en:	European Journal of Trauma & Emergency Surgery Vol. 50; no. 6; pp. 2819 - 2832
Autores principales:	Oude Nijhuis, Koen D., Dankelman, Lente H. M., Wiersma, Jort P., Barvelink, Britt, IJpma, Frank F.A., Verhofstad, Michael H. J., Doornberg, Job N., Colaris, Joost W., Wijffels, Mathieu M.E.
Formato:	diagnostic images research systematic review tables/charts Journal Article
Publicado:	Springer Nature Dec2024
Acceso en línea:	Ver este registro en EBSCOhost