/Heart-Failure-Prediction

This project predicts Cardiovascular Disorders (CVDs) using machine learning techniques, providing early detection and management insights based on health data and risk factors like hypertension and diabetes.

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Predicting Cardiovascular Disorders (CVDs) Using Machine Learning

Cardiovascular disorders (CVDs) are a significant cause of heart failure, affecting individuals with conditions such as hypertension, diabetes, and hyperlipidemia. Early detection and management are crucial for improving patient outcomes. This project aims to predict CVDs using machine learning techniques.

About the Project

This project focuses on developing a predictive model for Cardiovascular disorders (CVDs) based on various risk factors and health data. The goal is to classify individuals into two categories:

  • 1: Indicates the presence of heart failure (positive for CVDs).
  • 0: Indicates no heart failure (normal).