HeartWellness

Heart disease remains one of the leading causes of death globally, impacting millions of lives each year. Early detection and timely intervention are crucial in reducing the morbidity and mortality associated with heart conditions. Many healthcare providers and individuals lack access to advanced diagnostic tools that can analyze these factors effectively, leading to delayed diagnosis and treatment.

This project aims to develop an intelligent, data-driven solution that leverages machine learning algorithms to predict the risk of heart disease based on individual health metrics. By inputting key details such as blood pressure, age, sex, cholesterol levels, and other relevant factors, the system provides a reliable assessment of whether a person is likely to have heart disease. This tool can aid healthcare providers in early diagnosis and help individuals take proactive steps towards better heart health.