Machine Learning Applications for the Development of a Questionnaire to Identify Sasang Constitution Typology.

Kim, Soon Mi; Ryu, Jeongkun; Park, Eunhye Olivia

Kim, Soon Mi; Ryu, Jeongkun; Park, Eunhye Olivia.

Afiliación

Kim SM; Department of Food and Nutrition, College of BioNano Technology, Gachon University, Seongnam 13120, Korea.
Ryu J; Department of Food and Nutrition, College of BioNano Technology, Gachon University, Seongnam 13120, Korea.
Park EO; Department of Food and Nutrition, College of BioNano Technology, Gachon University, Seongnam 13120, Korea.

Int J Environ Res Public Health ; 19(18)2022 09 19.

Article en En | MEDLINE | ID: mdl-36142090

Asunto(s)

Aprendizaje Automático; Medicina Tradicional Coreana; Reproducibilidad de los Resultados; Encuestas y Cuestionarios

Palabras clave

Sasang constitution typology; Sasang constitutional medicine; feature selection; hierarchical clustering analysis; machine learning

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Medicina Tradicional Coreana / Aprendizaje Automático Tipo de estudio: Prognostic_studies Idioma: En Revista: Int J Environ Res Public Health Año: 2022 Tipo del documento: Article

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