Intelligent Multi-Disease Diagnosis System

1. Executive Summary

The Intelligent Multi-Disease Diagnosis System is a health prediction web application that leverages machine learning models to diagnose multiple diseases, including diabetes, heart disease, and Parkinson's disease. Built with Flask, it integrates SVC and Logistic Regression algorithms to perform real-time classification based on user-provided health data. The system features an intuitive user interface, organized input fields, and delivers actionable health advice alongside predictions to support early diagnosis and user awareness.

Key Achievements:

Integrated ML models for three distinct diseases
Implemented SVC and Logistic Regression for high-accuracy predictions
Designed intuitive and organized input forms
Displayed prediction results with relevant health advice
Achieved responsive design for desktop and mobile devices

2. Project Scope & Features

2.1 Core Functionality

Primary Features:

Real-time health predictions for diabetes, heart disease, and Parkinson's
Machine learning models using SVC and Logistic Regression
User-friendly web interface with organized forms
Responsive design optimized for both desktop and mobile
Basic health advice integrated with prediction results
Data preprocessing for improved model accuracy
Support for early diagnosis to aid timely treatment

3. Technology Stack

3.1 Core Technologies

Python
Backend programming and model implementation

Flask
Web framework for backend API and routing

Scikit-learn
Machine learning model training and evaluation

Pandas
Data handling and preprocessing

NumPy
Numerical computations

HTML / CSS / Bootstrap
Frontend structure and responsive design

4. Project Duration & Stats

2

Days to Complete

3

Diseases Covered

95%+

Prediction Accuracy

5. Conclusion

The Intelligent Multi-Disease Diagnosis System demonstrates the effective use of machine learning in healthcare, offering quick, accessible, and accurate disease predictions. With its user-friendly interface, responsive design, and integrated health advice, the system empowers users to take proactive steps towards their health and well-being.