Multiple disease prediction system

The Multiple Disease Prediction System is an AI-powered web application developed to assist in the early detection of various health conditions by predicting the likelihood of diseases such as diabetes, heart disease, Parkinson’s disease, and breast cancer based on user-inputted medical data. Users begin by selecting a disease from a dropdown menu, after which the interface dynamically generates a form requiring relevant clinical parameters such as age, blood pressure, glucose levels, BMI, cholesterol, or tremor intensity—depending on the selected disease. Once the user enters the required information and submits the form, the system processes the data using pre-trained machine learning models such as Logistic Regression, Random Forest, or Support Vector Machine, all trained on publicly available datasets from sources like Kaggle and UCI. The prediction result is displayed instantly, indicating whether the user is at high or low risk for the selected condition. Built using Python libraries including Streamlit for the frontend, scikit-learn for model inference, and pandas for data processing, the system runs locally and can be launched by cloning the repository, installing dependencies with pip install -r requirements.txt, and executing streamlit run app.py. This project is intended for educational and awareness purposes only and is not a replacement for professional medical evaluation or diagnosis.

Built With

• machine-learning
• python