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A journey toward artificial intelligence-assisted automated sleep scoring.
Chang, Rui B.
Afiliación
  • Chang RB; Department of Neuroscience, Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06520, USA.
Patterns (N Y) ; 3(1): 100429, 2022 Jan 14.
Article en En | MEDLINE | ID: mdl-35079722
Sleep scoring is a tedious, time-consuming process that presents a huge challenge in clinics. Leveraging the state-of-the-art U-net architecture, Zhang et al. developed a deep learning algorithm to simultaneously annotate basic and pathologic sleep stages. This model can analyze a full-length sleep record in a few seconds with high accuracy.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Patterns (N Y) Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Patterns (N Y) Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos