https://github.com/jonperron/med-assist

Med-Assist is an open-source tool that helps medical professionals extract key information—such as diseases, symptoms, and treatments—from clinical documents.
https://github.com/jonperron/med-assist

medical medical-applications nlp

Last synced: 9 months ago
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Med-Assist is an open-source tool that helps medical professionals extract key information—such as diseases, symptoms, and treatments—from clinical documents.

• Host: GitHub
• URL: https://github.com/jonperron/med-assist
• Owner: jonperron
• License: apache-2.0
• Created: 2025-06-17T12:05:00.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-09-20T12:27:17.000Z (9 months ago)
• Last Synced: 2025-09-20T13:22:30.686Z (9 months ago)
• Topics: medical, medical-applications, nlp
• Language: Python
• Homepage:
• Size: 466 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# 🩺 Med-Assist

[![Build Status](https://img.shields.io/github/actions/workflow/status/jonperron/med-assist/backend-ci.yml?branch=main)](https://github.com/your-org/med-assist/actions)

**Med-Assist** is an open-source tool that helps medical professionals extract key information—such as diseases, symptoms, and treatments—from clinical documents.

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## ⚠️ Disclaimer

> **Med-Assist is under active development.**

It is not intended for use in clinical decision-making and should not replace professional medical advice or diagnosis.

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## 🔐 Privacy & Data Control

- **Local-first by design**

  Med-Assist runs entirely on your infrastructure—no external APIs or cloud dependencies.

- **Secure storage**

  All data is stored in a local Redis instance, ensuring patient information remains private and compliant with data protection regulations.

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## 🌱 Green Impact

Med-Assist is built to run on minimal hardware, with a small footprint. It’s optimized to reduce energy usage and maximize sustainability—making it ideal for edge devices or local hospital servers.

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## 🧩 Project Structure

- [`backend/`](./backend/README.md) – FastAPI-based backend for processing and text extraction.

- [`frontend/`](./frontend/README.md) – Web interface to upload, manage, and visualize documents.

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## 🤝 Contributing

We welcome community contributions!

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## 📜 License

This project is licensed under the **Apache 2.0 License**.

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## 📚 References

This project builds upon the following resources:

- Labrak, Y., Bazoge, A., Dufour, R., Rouvier, M., Morin, E., Daille, B., & Gourraud, P.-A. (2023).

  **DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains.**

  *Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL'23), Long Paper*, Toronto, Canada.

  [ACL Anthology](https://aclanthology.org/)

- Grabar, N., Dalloux, C., & Claveau, V. (2020).

  **CAS: corpus of clinical cases in French.**

  *Journal of Biomedical Semantics, 11*, 7.

  [https://doi.org/10.1186/s13326-020-00225-x](https://doi.org/10.1186/s13326-020-00225-x)