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It’s optimized to reduce energy usage and maximize sustainability—making it ideal for edge devices or local hospital servers.\n\n---\n\n## 🧩 Project Structure\n\n- [`backend/`](./backend/README.md) – FastAPI-based backend for processing and text extraction.\n- [`frontend/`](./frontend/README.md) – Web interface to upload, manage, and visualize documents.\n\n---\n\n## 🤝 Contributing\n\nWe welcome community contributions!\n\n---\n\n## 📜 License\n\nThis project is licensed under the **Apache 2.0 License**.\n\n---\n\n## 📚 References\n\nThis project builds upon the following resources:\n\n- Labrak, Y., Bazoge, A., Dufour, R., Rouvier, M., Morin, E., Daille, B., \u0026 Gourraud, P.-A. (2023).\n  **DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains.**\n  *Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL'23), Long Paper*, Toronto, Canada.\n  [ACL Anthology](https://aclanthology.org/)\n\n- Grabar, N., Dalloux, C., \u0026 Claveau, V. (2020).\n  **CAS: corpus of clinical cases in French.**\n  *Journal of Biomedical Semantics, 11*, 7.\n  [https://doi.org/10.1186/s13326-020-00225-x](https://doi.org/10.1186/s13326-020-00225-x)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonperron%2Fmed-assist","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjonperron%2Fmed-assist","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonperron%2Fmed-assist/lists"}