Non-invasive method to analyse the risk of developing diabetic foot.

Silva, Rebeca N; Ferreira, Ana C B H; Ferreira, Danton D; Barbosa, Bruno H G

Silva, Rebeca N; Ferreira, Ana C B H; Ferreira, Danton D; Barbosa, Bruno H G.

Afiliación

Silva RN; Engineering Department , Federal University of Lavras , Lavras , Minas Gerais 3030/37200-000 , Brazil.
Ferreira AC; School of Nursing , Federal University of Juiz de Fora , Juiz de Fora , MG 36036-900 , Brazil.
Ferreira DD; Engineering Department , Federal University of Lavras , Lavras , Minas Gerais 3030/37200-000 , Brazil.
Barbosa BH; Engineering Department , Federal University of Lavras , Lavras , Minas Gerais 3030/37200-000 , Brazil.

Healthc Technol Lett ; 1(4): 109-13, 2014 Oct.

Article en En | MEDLINE | ID: mdl-26609394

Palabras clave

Euclidian distance; K-means clustering algorithm; automatic noninvasive method; computational processing; data classification; diabetes mellitus; diabetic foot; diabetic patients; diseases; foot complications; foot ulcer; health care; information vector; medical diagnostic computing; operational stage; patient diagnosis; pattern classification; pattern clustering; risk analysis; self-care; simulated data; social scope

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Healthc Technol Lett Año: 2014 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido

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