这是一个适用于各种临床用例的广泛网页应用。它有Flask服务器、React前端、用于多模型数据库的SurrealDB、LLM集成、MCP、RAG、OSCAR EMR......
概览
是一个集成临床平台，旨在支持现代医疗工作流程中的广泛用例。该项目结合灵活的后端架构、尖端人工智能工具和电子病历互操作性，旨在为医疗提供者、患者和研究人员提供统一且可扩展的界面。 目前还处于早期阶段，我会尽力参与，但如果有人偶然发现并发现它有很大的积极潜力，我愿意加大我的努力。 如果有人有任何新的想法、建议、问题、愿意贡献，或想表达对项目的一般兴趣，可以通过我个人资料中的电子邮件地址[[T0]与我联系。 我还为本仓库打开了讨论区，供任何想提出建议或表达兴趣的人使用。 另外，可以看看https://github.
概述（AI 翻译）
ArsMedicaTech 是一个集成临床平台，旨在支持现代医疗工作流程中的多种用例。该项目结合灵活的后端架构、尖端的人工智能工具和电子病历互操作性，旨在为医疗提供者、患者和研究人员提供统一且可扩展的界面。
关于对该项目兴趣的说明：目前仍处于早期阶段，我会尽力参与，但如果有人偶然发现并发现它有很大的积极作用，我愿意加大我的努力。
如果有人有任何新的想法、建议、问题、愿意贡献，或想表达对项目的一般兴趣，可以通过我个人资料中的电子邮件地址联系我。
我还为本仓库打开了讨论区，供任何想提出建议或表达兴趣的人使用。
另外，看看目前正在做什么，哪些待办事项。
关于本地运行应用，请参见：RUNNING_LOCALLY.md。
如需即时入职帮助和了解仓库，可以访问GitCompass。
🚀 宗旨与愿景
本页由 AI 翻译，技术细节请以原文为准。
README
以下为原文 README 节选，完整内容请查看原文。
ArsMedicaTech
ArsMedicaTech is an integrated clinical platform designed to support a wide range of use cases across modern healthcare workflows. Combining a flexible backend architecture with cutting-edge AI tools and EMR interoperability, the project aims to deliver a unified, extensible interface for providers, patients, and researchers.
A note about interest in this project: Right now it is still in early stages, and I contribute to it when I can, but if anyone stumbles upon this and finds that it has the potential to do a lot of good, I am willing to upscale my efforts.
If anyone has any new ideas, suggestions, questions, would like to contribute, or would like to express even a general interest in the project, I can be reached via the e-mail address in my profile .
I also opened up the Discussions section for this repository for anyone who would like to suggest anything or express any interest at all.
Also, check out to see what’s currently being worked on and what’s on the backlog.
On running the app locally, please see: RUNNING_LOCALLY.md.
For immediate onboarding assistance and getting to know the repo, check it out on GitCompass.
🚀 Purpose & Vision
ArsMedicaTech is built to support the evolving digital needs of healthcare. Its long-term vision is to:
- Bridge human decision-making and AI recommendations using LLMs with deterministic guardrails.
- Unify disparate data sources including patient records, medical ontologies, and clinical knowledge into a cohesive graph model.
- Enable modular, multimodal interaction via a modern UI for providers and patients alike.
- Serve as a developer-friendly testbed for experimentation and contribution in clinical informatics.
🧱 Tech Stack
| Layer | Technology |
|---|---|
| Frontend | React (soon to be converted to TypeScript) |
| Backend | Flask (Python) |
| Database | SurrealDB (multi-model support: graph, relational, document, key-value, full-text, etc.) |
| Infrastructure | Dockerized stack with Nginx, Oscar EMR, and SurrealDB containers |
| AI/ML Integration | OpenAI-compatible LLMs (planned: RAG, fine-tuning, prompt engineering) |
| EMR Integration | Dockerized OSCAR EMR instance (BC configuration currently supported) |
✅ Completed Features
🧠 Data Architecture
- [x] Graph schema for symptoms ↔ diagnoses ↔ treatments ↔ medications.
安装
docker run --name redis -d -p 6379:6379 redis:latest