PREDICTION OF HEART DISEASE USING MACHINE LEARNING TECHNIQUES

PREDICTION OF HEART DISEASE USING MACHINE LEARNING TECHNIQUES

Dr. A. Haritha¹, M. Priyanka2, A. Bindu Priya Darshini3, I. Sumanth4, G. Amrutha5

Associate Professor, Department of Information Technology¹

B.Tech Students, Department of Information Technology^2,3,4,5

Prasad V Potluri Siddhartha Institute of Technology, Vijayawada,

Andhra Pradesh, India.

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Abstract: A severe and common medical problem that many people experiencing now-a- days is heart disease. Early identification and evaluation of heart disease is essential for avoiding further complications. The diagnosis of cardiac disease using conventional techniques may not always be precise or effective, though. A software program that uses machine learning to reliably and effectively estimate the risk of heart disease is thus required. This software helps in the early detection of heart disease. The suggested system for predicting heart disease using machine learning algorithms includes the Heart Disease Prediction Module as a critical element. Based on a variety of characteristics, including age, gender, blood pressure, cholesterol level, and other health metrics, this module is in charge of predicting heart disease for a specific patient.

Keywords: Logistic Regression, Random Forest, Decision Tree, KNN.