Using Grip Strength as a Cardiovascular Risk Indicator Based on Hybrid Algorithms
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 car...
Saved in:
Published in | International journal of interactive multimedia and artificial intelligence Vol. 7; no. 2; pp. 27 - 33 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
IMAI Software
01.12.2021
Universidad Internacional de La Rioja (UNIR) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | 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. KEYWORDS Body Mass Index, C-Means, K-Means, Percentage F Fat, Prehensile Strength, Risk Indicator, Support Vector Machine. |
---|---|
ISSN: | 1989-1660 1989-1660 |
DOI: | 10.9781/ijimai.2021.05.004 |