Machine learning seizure prediction: one problematic but accepted practice.

West, Joseph; Dasht Bozorgi, Zahra; Herron, Jeffrey; Chizeck, Howard J; Chambers, Jordan D; Li, Lyra

West, Joseph; Dasht Bozorgi, Zahra; Herron, Jeffrey; Chizeck, Howard J; Chambers, Jordan D; Li, Lyra.

Afiliação

West J; School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia.
Dasht Bozorgi Z; Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
Herron J; School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia.
Chizeck HJ; Department of Neurological Surgery, University of Washington, Seattle, Washington, United States of America.
Chambers JD; Department of Electrical and Computer Engineering, University of Washington, Seattle, Washington, United States of America.
Li L; Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.

J Neural Eng ; 20(1)2023 01 18.

Article em En | MEDLINE | ID: mdl-36548993

Assuntos

Epilepsia; Qualidade de Vida; Humanos; Convulsões/diagnóstico; Epilepsia/diagnóstico; Aprendizado de Máquina; Eletroencefalografia/métodos

Palavras-chave

deep learning; epilepsy; machine learning; seizure prediction; supervised learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Epilepsia Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Neural Eng Assunto da revista: NEUROLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália

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