مشروع توقع الأمراض حسب الاعراض python

? Exploring AI for Symptom Analysis

Rule-based systems are limited when real-world symptoms overlap or are incomplete. I built an experimental web-based system that uses machine learning to analyze user-selected symptoms and suggest possible medical conditions probabilistically and explainably.

Key features:

Learns symptom–disease relationships from data

Handles incomplete or overlapping symptom sets

Produces ranked predictions with probabilities

Explains why each prediction appears

How it works:

1️⃣ Users select symptoms from categories (neurological, respiratory, digestive, etc.)

2️⃣ The system processes inputs with a trained ML model

3️⃣ Returns top conditions with confidence scores and match percentages

4️⃣ Results are presented visually, highlighting higher-risk cases

Technologies: Python, Flask, scikit-learn (RandomForest), pickle, HTML/CSS/JS

Example scenarios:

Differentiating Flu vs COVID-19 with overlapping symptoms

Handling partial symptom input (e.g., fatigue + shortness of breath)

Explaining why 100% symptom match ≠ highest probability

This project combines backend engineering, data-driven decision making, and explainable AI, keeping the UX clean and intuitive.

⚠️ For educational and experimental purposes onl