Medical Document Summarizer - Project Description

This is a production-ready, full-stack medical document processing system that combines artificial intelligence with military-grade encryption to help healthcare facilities digitize and analyze patient documents completely offline. The application accepts medical files in 18+ formats (PDFs, images, Word documents) and runs them through an intelligent 5-node AI pipeline that extracts text via OCR, automatically redacts sensitive information, performs medical entity recognition using spaCy, and generates comprehensive clinical summaries using the Mistral-7B large language model—all without internet connectivity.

Built with a modern tech stack featuring FastAPI backend, Next.js 14 TypeScript frontend, and an alternative Streamlit interface, the system implements zero-knowledge encryption where every piece of patient data is encrypted with AES-256-GCM before storage, ensuring even the server cannot access unencrypted information. A standout feature is the integrated end-to-end encrypted chat system using Signal Protocol, enabling medical teams to securely discuss cases and collaborate in real-time with messages that are encrypted client-side and never readable by the server.

The application runs entirely on local hardware with no cloud dependencies, making it ideal for privacy-conscious medical facilities. It supports offline team collaboration via Mobile Hotspot networking, includes text-to-speech audio generation, maintains encrypted processing history with configurable retention policies, and provides comprehensive API documentation. With over 14,000 lines of code, 40+ Python dependencies, and professional GitHub documentation, this system delivers enterprise-grade security, HIPAA-ready architecture, and AI-powered medical document analysis in a complete offline package ready for deployment in hospitals and clinics requiring maximum patient data protection.