Learning to detect the onset of slow activity after a generalized tonic-clonic seizure.

Vance, Carroll; Kim, Yejin; Zhang, Guoqiang; Lhatoo, Samden; Tao, Shiqiang; Cui, Licong; Li, Xiaojin; Jiang, Xiaoqian

Vance, Carroll; Kim, Yejin; Zhang, Guoqiang; Lhatoo, Samden; Tao, Shiqiang; Cui, Licong; Li, Xiaojin; Jiang, Xiaoqian.

Afiliación

Vance C; University of Houston, Houston, TX, USA. cs.vance@icloud.com.
Kim Y; School of Biomedical Informatics, UT Health, 7000 Fannin St Suite 600, Houston, TX, USA.
Zhang G; School of Biomedical Informatics, UT Health, 7000 Fannin St Suite 600, Houston, TX, USA.
Lhatoo S; Department of Neurology, McGovern Medical School, UT Health, 6430 Fannin St, Houston, TX, USA.
Tao S; Department of Neurology, McGovern Medical School, UT Health, 6430 Fannin St, Houston, TX, USA.
Cui L; School of Biomedical Informatics, UT Health, 7000 Fannin St Suite 600, Houston, TX, USA.
Li X; Department of Neurology, McGovern Medical School, UT Health, 6430 Fannin St, Houston, TX, USA.
Jiang X; School of Biomedical Informatics, UT Health, 7000 Fannin St Suite 600, Houston, TX, USA.

BMC Med Inform Decis Mak ; 20(Suppl 12): 330, 2020 12 24.

Article en En | MEDLINE | ID: mdl-33357225

Asunto(s)

Epilepsia; Convulsiones; Muerte Súbita; Electroencefalografía; Humanos; Convulsiones/diagnóstico; Convulsiones/terapia

Palabras clave

Convolutional neural network; Data paucity; Deep learning; Electroencephalogram; Generalized tonicclonic seizure; Machine learning; Neural network; Onset of slow activity; Signal detection; Sudden death in epilepsy

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Convulsiones / Epilepsia Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

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