An intelligent recommendation system that transforms healthcare through personalized AI-powered suggestions. Our system analyzes comprehensive health profiles to deliver tailored medical advice, improving patient outcomes and healthcare efficiency.
| Feature | Description | Technology Used |
|---|---|---|
| 🧪 Personalized Treatment | AI-curated treatment plans based on medical history | Scikit-learn, XGBoost |
| 💊 Smart Medication Advisor | Drug recommendations with allergy and interaction checks | Knowledge Graphs |
| 👨⚕️ Provider Matching | Doctor/specialist matching with patient needs | Cosine Similarity |
| 🥗 Lifestyle Coach | Custom diet & exercise plans | NLP, Clinical Guidelines |
| 🤒 Symptom Analyzer | Preliminary diagnosis from symptoms | Neural Networks |
Core Components:
- 🧠 AI Engine: Scikit-learn, TensorFlow
- 📊 Data Processing: Pandas, NumPy
- 🌐 API Layer: Flask with Swagger docs
- 🗄️ Database: PostgreSQL
- 📱 Frontend: React.js dashboard
- Python 3.8+
- Clinical dataset (synthetic or approved real data)
# Clone with authentication submodule
git clone --recurse-submodules https://github.com/adam-ben-rhaiem/Healthcare-Recommendation-System.git
# Set up environment
cd healthcare-recommendation-system
python -m venv .venv
source .venv/bin/activate # Linux/Mac
# .venv\Scripts\activate # Windows
# Install with pip
pip install -r requirements.txt
# Set up environment variables
cp .env.example .env