Machine Learning Methods to Predict Diabetes Complications.

Dagliati, Arianna; Marini, Simone; Sacchi, Lucia; Cogni, Giulia; Teliti, Marsida; Tibollo, Valentina; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

Dagliati, Arianna; Marini, Simone; Sacchi, Lucia; Cogni, Giulia; Teliti, Marsida; Tibollo, Valentina; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo.

Afiliación

Dagliati A; 1 Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Marini S; 2 Centre for Health Technologies, University of Pavia, Pavia, Italy.
Sacchi L; 3 IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Pavia, Italy.
Cogni G; 1 Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Teliti M; 2 Centre for Health Technologies, University of Pavia, Pavia, Italy.
Tibollo V; 3 IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Pavia, Italy.
De Cata P; 1 Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Chiovato L; 2 Centre for Health Technologies, University of Pavia, Pavia, Italy.
Bellazzi R; 3 IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Pavia, Italy.

J Diabetes Sci Technol ; 12(2): 295-302, 2018 03.

Article en En | MEDLINE | ID: mdl-28494618

Asunto(s)

Algoritmos; Minería de Datos/métodos; Complicaciones de la Diabetes; Diabetes Mellitus Tipo 2/complicaciones; Aprendizaje Automático; Humanos

Palabras clave

Data Mining; Machine Learning; Microvascular Complications; Risk Predictions; Type 2 Diabetes

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Complicaciones de la Diabetes / Diabetes Mellitus Tipo 2 / Minería de Datos / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Diabetes Sci Technol Asunto de la revista: ENDOCRINOLOGIA Año: 2018 Tipo del documento: Article País de afiliación: Italia

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