MULTIPLEDISEASE PREDICTION SYSTEM

Effective treatment of disease including diabetes, heart disease, and Parkinson\\\'s depends on early detection. Traditional methods can take a long time and result in a delayed diagnosis. The goal of this research is to create a machine learning-based system that can accurately predict diseases. A Support Vector Machine (SVM) was initially used, but its accuracy was poor. So Convolutional Neural Network (CNN) was used to improve performance, which achieved significantly higher accuracy in both training and testing. The results show CNN\\\'s effectiveness in medical diagnostics, providing a dependable method for early detection. Future research can focus on expanding datasets and real-time clinical applications.