Estimating Heart Disease Used by Data Mining and Artificial Intelligence Techniques
International Journal of Computer Science and Engineering |
© 2023 by SSRG - IJCSE Journal |
Volume 10 Issue 4 |
Year of Publication : 2023 |
Authors : R. Surendiran |
How to Cite?
R. Surendiran, "Estimating Heart Disease Used by Data Mining and Artificial Intelligence Techniques," SSRG International Journal of Computer Science and Engineering , vol. 10, no. 4, pp. 1-7, 2023. Crossref, https://doi.org/10.14445/23488387/IJCSE-V10I4P101
Abstract:
The heart is the most dangerous and significant part of the human physique. Life is entirely reliant upon the healthy operation of our hearts. It is a significant cause of death in the modern biosphere. One of the most critical health problems facing people today is heart illness. It is reportedly the leading cause of demise around the globe. Medical specialists frequently find it challenging to predict a cardiac illness early on. Many valuable hidden facts and information in the health sector today might be used to make predictions, particularly in treatment. Data mining remains a process for examining massive datasets before producing substantial and practical outcomes using exceptional AI-based apparatuses. This article aims to anticipate cardiovascular or heart illness using 3 AI devices Decision tree, naive Bayes, and a neural system. These techniques' determination is assessed based on many particular & factors with improvements for greater accuracy. The correctness based on various characteristics of each approach will then be compared. Afterwards, the most reliable method determines whether a man or woman resolves to develop coronary heart ailment. Medical professionals can utilize this method to anticipate diseases early so that prompt treatment can the given if he is persevering.
Keywords:
Data mining, Artificial intelligence, Heart, Illness, Estimate.
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