Development of a deep learning algorithm for radiographic detection of syndesmotic instability in ankle fractures with intraoperative validation

Abstract Identifying syndesmotic instability in ankle fractures using conventional radiographs is still a major challenge. In this study we trained a convolutional neural network (CNN) to classify the fracture utilizing the AO-classification (AO-44 A/B/C) and to simultaneously detect syndesmosis ins...

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Bibliografische gegevens

Hoofdauteurs:	Joshua Kubach, Tobias Pogarell, Michael Uder, Mario Perl, Marcel Betsch, Mario Pasurka, Stefan Söllner, Rafael Heiss
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Nature Portfolio 2025-08-01
Reeks:	Scientific Reports
Online toegang:	https://doi.org/10.1038/s41598-025-14604-w
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