🩺 HealthHacked: AI-Powered Symptom Checker & Triage Assistant

HealthHacked is a smart healthcare assistant that allows users to:

• Describe their symptoms in natural language
• Receive likely medical conditions with confidence scores
• Get urgency recommendations (e.g., rest at home, visit a GP, or go to the ER)
• Track symptoms over time and receive pattern-based follow-ups

Built for the Hack4Health 2025 Hackathon under the Advanced Division.

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🔍 Problem Statement

Healthcare access is often delayed due to uncertainty and lack of awareness. People Google their symptoms, panic unnecessarily, or worse—ignore warning signs. HealthHacked bridges this gap by offering:

• AI-powered, interpretable suggestions
• Personalized triage decisions
• Symptom tracking and historical pattern recognition

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💡 Key Features

🧠 AI Symptom Analysis

• NLP-based symptom extraction
• TF-IDF + Logistic Regression classifier
• Predicts possible conditions with confidence scores

🚨 Triage Recommendation

• Rule-based decision engine to recommend next steps:
  • Try rest & hydration
  • Book GP appointment
  • Seek ER immediately

📊 Symptom Tracker & Pattern Detector

• Logs symptom data per user
• Detects patterns like:
  • Recurrent headaches
  • Seasonal triggers
  • Worsening trends over time

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🏗️ Architecture

User Input → NLP Processing → Symptom Classifier →
Triage Engine → Recommendation + Storage →
Pattern Detection → Follow-up Advice

🧱 Tech Stack

Layer	Tech
Backend	FastAPI, scikit-learn, spaCy
Frontend	Handled by teammates (HTML/CSS + JS)
Database	SQLite (MVP-friendly)
Model Storage	Pickle (.pkl) for trained ML
Hosting	Render / Railway (free tiers)

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📁 Folder Structure

HealthHacked/
├── app/
│   ├── main.py                # FastAPI app
│   ├── models/                # ML + triage logic
│   ├── services/              # NLP, recommendations
│   ├── api/                   # API routes
│   └── data/                  # Datasets
├── database/                  # SQLite DB
├── run.py                     # Entry point
├── requirements.txt
└── .gitignore

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🧪 API Demo

Endpoint: POST /api/analyze-symptoms

Sample Input:

{
  "symptoms": "I have chest tightness and shortness of breath",
  "severity": 7,
  "duration": "2 days",
  "user_id": "demo_user"
}

Sample Output:

{
  "predicted_conditions": [
    {"condition": "Angina", "confidence": 0.62},
    {"condition": "Heart Attack", "confidence": 0.25}
  ],
  "urgency": "Seek emergency care immediately",
  "next_steps": "Call emergency services or go to the nearest ER."
}

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⏳ Timeline Breakdown (20-Day MVP)

Week	Milestone
1	FastAPI setup, dataset preprocessing, baseline ML model
2	API endpoints, triage logic, database integration
3	Pattern detection, UI integration, deployment

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👨‍💻 Contributors

• AI & Backend – Hammad Malik
• Frontend – KLN Sai Aditya & Ayushmaan Manish Kumar

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🚀 Try It Yourself

git clone https://github.com/your-username/HealthHacked.git
cd HealthHacked
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
python run.py

Visit: http://127.0.0.1:8000/docs to test the interactive API.

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✅ Future Scope

• Migrate to advanced transformers (DistilBERT)
• Add real-time vitals via wearable API
• Multi-language symptom support
• Secure authentication + user dashboard

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🏁 License

This project is built for educational and prototype purposes under the MIT License.

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Let’s hack health, one symptom at a time. 💻💉