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

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.

• 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.

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.

• backend/ – FastAPI-based backend for processing and text extraction.
• frontend/ – Web interface to upload, manage, and visualize documents.

We welcome community contributions!

This project is licensed under the Apache 2.0 License.

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

• 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