Multiple Disease Prediction System Using Machine Learning

The Multiple Disease Prediction System (MDPS) employs machine learning techniques—specifically Support Vector Machines (SVM) and Logistic Regression—to detect various diseases within a single platform. This system is implemented using the Django web framework, offering a user-centric interface for improved accessibility. The primary goal is to support early disease detection and encourage personalized healthcare solutions. The system focuses on predicting diabetes, heart disease, and Parkinson’s disease based on health indicators such as cholesterol levels, heart rate, pulse rate, and blood pressure. Through the use of accurate and efficient ML models, this approach identifies risk factors for multiple illnesses simultaneously. While individual disease prediction models are common, this study presents an integrated solution to predict several diseases at once. The proposed system demonstrates the effectiveness of machine learning in enhancing diagnostic capabilities and promoting better health outcomes.