Heart Attack Predication Using Machince Learning

Abstract

The heart, often referred to as the body's pump, is crucial for circulating oxygenated and deoxygenated blood to all organs. Achieving precision and accuracy in diagnosing and analyzing heart conditions is imperative for timely intervention. This study employs Python programming language and machine learning techniques, utilizing libraries such as NumPy, Pandas, among others, to investigate the Multiple factors including blood pressure, blood sugar, and cholesterol levels contribute to the occurrence of heart attacks. The dataset comprises 14 elements, each representing individual values crucial for patient analysis. The primary objective of this research is to achieve maximum accuracy in heart attack detection through machine learning algorithms