ARCHIVES

Abstract: The Multi Disease Prediction System (MDPS) utilizes machine learning techniques, particularly Logistic Regression and Support Vector Machines (SVM), to forecast various illnesses including diabetes, heart disease, and Parkinson's disease. It employs a user-friendly interface developed with Streamlit, enhancing accessibility. By analysing standard health indicators such as blood pressure, pulse rate, cholesterol, and heart rate, the system aims to improve early detection and enable personalized healthcare. The model demonstrates notable accuracy and precision, aiding in the identification of critical risk factors associated with these ailments. This paper highlights the essential role of machine learning in simultaneously predicting multiple diseases, addressing a current gap in technological capabilities. The project underscores the advancement of disease prediction through sophisticated machine learning methodologies.