Using Grip Strength as a Cardiovascular Risk Indicator Based on Hybrid Algorithms

Author
Keywords
Abstract
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.
Year of Publication
9998
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
In Press
Issue
In Press
Number
In Press
Number of Pages
1-7
Date Published
05/2021
ISSN Number
1989-1660
URL
https://www.ijimai.org/journal/sites/default/files/2021-05/ip2021_05_04.pdf
DOI
10.9781/ijimai.2021.05.004
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