A self-supervised learning-based approach to clustering multivariate time-series data with missing values (SLAC-Time): An application to TBI phenotyping.

Ghaderi, Hamid; Foreman, Brandon; Nayebi, Amin; Tipirneni, Sindhu; Reddy, Chandan K; Subbian, Vignesh

Ghaderi, Hamid; Foreman, Brandon; Nayebi, Amin; Tipirneni, Sindhu; Reddy, Chandan K; Subbian, Vignesh.

Afiliación

Ghaderi H; Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA. Electronic address: ghaderi@arizona.edu.
Foreman B; College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
Nayebi A; Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA.
Tipirneni S; Department of Computer Science, Virginia Tech, Arlington, VA, USA.
Reddy CK; Department of Computer Science, Virginia Tech, Arlington, VA, USA.
Subbian V; Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA; Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA.

J Biomed Inform ; 143: 104401, 2023 07.

Article en En | MEDLINE | ID: mdl-37225066

Asunto(s)

Lesiones Traumáticas del Encéfalo; Humanos; Lesiones Traumáticas del Encéfalo/diagnóstico; Análisis por Conglomerados; Factores de Tiempo; Unidades de Cuidados Intensivos; Aprendizaje Automático Supervisado

Palabras clave

Clustering; Multivariate time-series data; Self-supervised learning; Transformer; Traumatic brain injury

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lesiones Traumáticas del Encéfalo Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

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