AI-Powered Disease Prediction Web App Using Machine Learning

Overview

The Disease Prediction Web Application is a powerful tool designed to help users identify potential illnesses based on selected symptoms. Utilizing advanced machine learning algorithms like Random Forest and Naive Bayes, this app delivers accurate predictions with probability scores, enabling informed decision-making.

Key Features

• Interactive Symptom Selection: Search and choose from an extensive list of symptoms with real-time filtering.
• Severity Weighted Predictions: Symptoms are weighted by severity to enhance prediction accuracy.
• Top 3 Disease Predictions: Both models provide top 3 possible diseases along with confidence percentages.
• Mobile Responsive Design: Works seamlessly across desktops, tablets, and smartphones.
• Real-Time Filtering: Instant symptom search improves usability and speed.

Applications

This application can be used in various scenarios including:

• Educational platforms for teaching AI/ML concepts.
• Preliminary diagnosis tools for healthcare startups.
• Personal health awareness applications.
• Research projects in the field of medical AI.

Technology Stack

Built using modern technologies, the backend runs on Flask while the frontend uses HTML, CSS Grid, and JavaScript for dynamic interaction. Two trained models ensure high performance and reliability.

Why Choose This Project?

Whether you're a developer looking to explore machine learning or a student working on a capstone project, this disease prediction system offers a perfect blend of functionality, simplicity, and educational value. It's ready to deploy, fully customizable, and comes with detailed documentation.