Heart Disease Prediction Using Machine Learning

Heart Disease Prediction Using Machine Learning

Nikkitha G1, Nivedha N2, Raama Nivethaa D3, Sree Harshini S4, Mrs.R Divya5

1, 2, 3, 4UG Scholars, 5Assistant Professor, Department of Computer Science and Engineering,

Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering, Coimbatore, India

ABSTRACT

Heart failure is a chronic disease affecting millions worldwide. An efficient machine learning- based technique is needed to predict heart failure health status early and take necessary actions to overcome this worldwide issue. The study addresses data preparation difficulties such as missing values and outliers by leveraging a large dataset including critical health parameters such as age, gender, blood pressure, and cholesterol levels. The models are trained using this new dataset, and the anticipated performance is rigorously assessed using standard criteria. The study includes a detailed review of the Warm and Naive Bayes (NB) models, highlighting their benefits and drawbacks in the context of heart disease prediction. Our proposed research study has significant scientific contributions to the medical community.

Keywords: Heart Disease, Machine Learning, Predictive Modeling, Medical History