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Heart Risk Assessment Analysis and Prediction using Various Machine Learning Algorithms

Journal: International Journal of Information Systems and Computer Sciences (IJISCS) (Vol.12, No. 6)

Publication Date:

Authors : ;

Page : 37-41

Keywords : Logistic-Regression; Decision-Tree; KNN; Naïve-Bayes; Neural-Networks; Random-Forest; Support- Vector-Machine; XG-Boost;

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Abstract

N today's world artificial intelligence plays a major and crucial role in technological development. Machine Learning is an extension of Artificial Intelligence through which accuracy and prediction rate of model is made without the assist of any external programs. The evolution andopportunity of ML is expandingeach and every day. Many organizations have made ML as one the important assets of their company.Supervised, Unsupervised and Reinforcement learning and ensemble learning's are different types of ML through which datasets accuracy can be measured. Our current study focuses mainly on Utilizationof ML in medical industry. Based on current report of World Health Organization the most predominant cause of death is detecting most on cardiovascular disease. Myocardial infarction also said as heart attack is caused when flood flow to the heart muscles has been suddenly blocked. It should be considered as the severe one detection should be done in early stage so life can be prevented. This article presentsaexamination on machine learning for projection of heart disease. Distinct expert algorithms have been used for the evaluation and model deployment purpose

Last modified: 2023-12-17 22:50:00