Early Health Risk Screening

The Pre-Disease Predictor is a comprehensive web application designed to predict multiple diseases based on user-provided symptoms and health metrics. Leveraging machine learning models, it provides predictions for diabetes, heart disease, and various other conditions. The application is primarily built using Python, with Streamlit employed to create an interactive user interface. For data manipulation and analysis, the Pandas library is utilized. The machine learning models are implemented using Scikit-learn. A novel feature of this project is its ability to provide immediate disease predictions with an accuracy of $85 \%$. For diabetes prediction, the application uses a Support Vector Machine (SVM) classifier, while a Random Forest Classifier is employed for heart disease and multiple disease predictions. The application reads data from CSV files for training and testing the models, including diabetes.csv for diabetes prediction, heart.csv for heart disease prediction, and Training.csv and Testing.esv for multiple disease prediction.