Using Grip Strength as a Cardiovascular Risk Indicator Based on Hybrid Algorithms
Autor:
Bareño-Castellanos, E.F.
; Gaona-García, Paulo Alonso
; Ortiz-Guzmán, J.E.
; Montenegro-Marin, Carlos Enrique
Fecha:
12/2021Palabra clave:
Revista / editorial:
International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)Tipo de Ítem:
articleDirección web:
https://www.ijimai.org/journal/bibcite/reference/2947Resumen:
This article shows the application and design of a hybrid algorithm capable of classifying people into risk groups using data such as prehensile strength, body mass index and percentage of fat. The implementation was done on Python and proposes a tool to help make medical decisions regarding the cardiovascular health of patients. The data were taken in a systematic way, k-means and c-means algorithms were used for the classification of the data, for the prediction of new data two vectorial support machines were used, one for the k-means and the other for the c-means, obtaining as a result a 100% of precision in the vectorial support machine with c-means and a 92% in the one of k-means.
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