This project is a AI-based healthcare assistant designed to help users:

• Understand their symptoms
• Analyze uploaded medical reports
• Get guidance on which medical department to consult
• Identify potential emergency situations early

⚠️ Disclaimer:
This system is *not a medical diagnosis tool. It is intended *only for educational and experimental purposes and should not replace professional medical advice.

• Users enter:
  • Symptoms
  • Lab test results / report findings
• The system:
  • Retrieves similar historical patient cases from a local vector database
  • Uses semantic similarity (embeddings)
  • Suggests:
    • Relevant hospital department

• Upload any medical report (text-based)
• AI extracts and summarizes:
  • Key findings
  • Report Summary(Hindi/English)
• Helps users understand complex reports in simple language

User Input
Streamlit Frontend
↓
Backend Logic (Python)
↓
Chunking (Symptoms / Clinical / Assessment)
↓
AI Embeddings
↓
In-Memory Vector Store
↓
Similarity Retrieval + Rules
↓
Application Logic Response

User Input
↓
Symptoms + Reports
↓
NLP(AI Embeddings + Symantec Similarity)
↓
Report Analyzer
↓
AI Triage Engine
↓
Department Mapping
↓
Nearby Hospital Matching ↓
Doctor Recommendation + Directions

1️⃣ Clone the repository

git clone https://github.com/Harshcoder9/AIXMedTech-hackathon.git

cd AIXMedTech-hackathon

2️⃣ Install dependencies

pip install -r requirements.txt

3️⃣ Run the Streamlit app

streamlit run landing.py

PLEASE WAIT FOR FEW MINUTES BEFORE THE APPLICATION BECOMES FULLY OPERATIONAL AND YOU WOULD GET BELOW LANDING PAGE - As hospital patients vector database building takes few minutes.