SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models

Abstract Automatic sleep staging with deep learning has advanced considerably, yet clinical adoption remains hindered by limited generalization, model bias, and inconsistent evaluation practices. We present SLEEPYLAND, an open-source framework comprising ~ 220,000 h of in-domain and ~ 84,000 h of ou...

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Auteurs principaux:	Alvise Dei Rossi, Matteo Metaldi, Michal Bechny, Irina Filchenko, Julia van der Meer, Markus H. Schmidt, Claudio L. A. Bassetti, Athina Tzovara, Francesca D. Faraci, Luigi Fiorillo
Format:	Artigo
Langue:	Inglês
Publié:	Nature Portfolio 2025-12-01
Collection:	npj Digital Medicine
Accès en ligne:	https://doi.org/10.1038/s41746-025-02237-2
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