This project provides a streamlit web application for predicting multiple diseases, including diabetes, Parkinson's disease, and heart disease, eye disease using machine learning algorithms. The prediction models are deployed using Streamlit, a Python library for building interactive web applications.
The Multiple Disease Prediction project aims to create a user-friendly web application that allows users to input relevant medical information and receive predictions for different diseases. The machine learning models trained on disease-specific datasets enable accurate predictions for diabetes, Parkinson's disease, and heart disease.
The Multiple Disease Prediction web application offers the following features:
- User Input: Users can input their medical information, including age, gender, blood pressure, cholesterol levels, and other relevant factors.
- Disease Prediction: The application utilizes machine learning models to predict the likelihood of having diabetes, Parkinson's disease, and heart disease based on the inputted medical data.
- Prediction Results: The predicted disease outcomes are displayed to the user, providing an indication of the probability of each disease.
- Visualization: Visualizations are generated to highlight important features and provide insights into the prediction process.
- User-Friendly Interface: The web application offers an intuitive and user-friendly interface, making it easy for individuals without technical knowledge to use the prediction tool.