Interpretable deep learning for rotator cuff calcific tendinopathy diagnosis: a multi-center study

Abstract The reliable deployment of artificial intelligence systems in medical imaging requires high diagnostic performance, robustness and interpretability. In this study, we developed and evaluated two automated frameworks for binary classification of shoulder radiographs (XRs) using deep learning...

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Autores principales:	Juan Miranda Bautista, Javier Llorente Peris, Fernando Ybáñez Carrillo, Lara Lloret Iglesias, José A. Vega, Pablo Menéndez Fernández-Miranda
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Nature Portfolio 2026-06-01
Colección:	Scientific Reports
Acceso en línea:	https://doi.org/10.1038/s41598-026-51016-w
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