Machine Learning-Based Disease Prediction

Disease prediction and early diagnosis are pivotal in improving healthcare outcomes and reducing the burden of chronic illnesses. In this research, we present an innovative approach to disease prediction using the Random Forest algorithm, implemented within a user-friendly Streamlit frontend application. Our study focuses on the prediction of five significant diseases: diabetes, heart disease, liver disease, kidney disease, and Parkinson’s disease