A Review on Heart Disease Prediction and Evaluation Using Machine Learning Algorithms

B. Nitesh, V. Kalpana and M. Sushmasri

International Journal of Scientific Research in Science and Technology, 2025, vol. 12, issue 2, 410-417

Abstract: Now a days the main difficult task in the medical field is to diagnosis the heart disease which relies on decision by grouping of large clinical and pathological data. Also, there is a significance about efficiency and accuracy between researchers and clinical professionals in diagnosis and prediction of heart related diseases because correct diagnosis at early stage leads to make a human alive. Thus, in recent years the proliferation in Machine Learning evolves in supporting in medical domain for predicting disease by training and testing the datasets. So, the main aspect behind our work is to study on diverse prediction models for the heart disease and selecting important heart disease feature using different algorithms based on different datasets. And also, by using project there will be need of prediction system for awareness about heart disease. In this project, we calculate accuracy of some widely used Machine Learning algorithms for predicting heart disease. Based on predications using different Machine Learning algorithms we are going to predict condition of a person related to heart.

Keywords: Machine Learning; Python; Modules; Packages (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v12:y2025:i2:id:681

DOI: 10.32628/IJSRST25122243

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