Application of Machine Learning to Sleep Stage Classification.

Smith, Andrew; Anand, Hardik; Milosavljevic, Snezana; Rentschler, Katherine M; Pocivavsek, Ana; Valafar, Homayoun

Smith, Andrew; Anand, Hardik; Milosavljevic, Snezana; Rentschler, Katherine M; Pocivavsek, Ana; Valafar, Homayoun.

Afiliación

Smith A; Department of Computer Science and Engineering (University of South Carolina), Columbia, SC 29208 USA.
Anand H; Department of Computer Science and Engineering (University of South Carolina), Columbia, SC 29208 USA.
Milosavljevic S; Department of Pharmacology, Physiology, and Neuroscience University of South Carolina School of Medicine, Columbia, SC 29208 USA.
Rentschler KM; Department of Pharmacology, Physiology, and Neuroscience University of South Carolina School of Medicine, Columbia, SC 29208 USA.
Pocivavsek A; Department of Pharmacology, Physiology, and Neuroscience University of South Carolina School of Medicine, Columbia, SC 29208 USA.
Valafar H; Department of Computer Science and Engineering (University of South Carolina), Columbia, SC 29208 USA.

Proc (Int Conf Comput Sci Comput Intell) ; 2021: 349-354, 2021 Dec.

Article en En | MEDLINE | ID: mdl-36313065

Palabras clave

artificial intelligence; electrophysiology; machine learning; neuroscience; sleep-scoring

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Proc (Int Conf Comput Sci Comput Intell) Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos

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