构建多语言隐私优先的医疗智能体系统，支持安全诊疗交互
Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
- 用MCP协议协调多个智能体完成问诊、用药建议与预约
- 通过字段级加密和权限控制满足HIPAA等合规标准
- 适合研究医疗AI安全与多语言应用的开发者参考
本文提出Agentic-AI Healthcare，一个由单人研究者开发的隐私敏感、多语言且可解释的研究原型。系统基于新兴的模型上下文协议（MCP），协调多个智能体实现患者交互，包括症状检查、药物建议和预约安排。平台集成专用隐私与合规层，采用基于角色的访问控制（RBAC）、AES-GCM字段级加密及防篡改审计日志，符合美国HIPAA、加拿大PIPEDA及安大略省PHIPA等主要医疗数据保护标准。示例用例展示了英文、法语、阿拉伯语的多语言医患交互，以及基于大语言模型的透明诊断推理。作为应用型AI贡献，本工作验证了智能体编排、多语言可达性与合规架构在医疗应用中的可行性。该平台为研究原型，非认证医疗设备。
原文摘要 · Abstract (English)
This paper introduces Agentic-AI Healthcare, a privacy-aware, multilingual, and explainable research prototype developed as a single-investigator project. The system leverages the emerging Model Context Protocol (MCP) to orchestrate multiple intelligent agents for patient interaction, including symptom checking, medication suggestions, and appointment scheduling. The platform integrates a dedicated Privacy and Compliance Layer that applies role-based access control (RBAC), AES-GCM field-level encryption, and tamper-evident audit logging, aligning with major healthcare data protection standards such as HIPAA (US), PIPEDA (Canada), and PHIPA (Ontario). Example use cases demonstrate multilingual patient-doctor interaction (English, French, Arabic) and transparent diagnostic reasoning powered by large language models. As an applied AI contribution, this work highlights the feasibility of combining agentic orchestration, multilingual accessibility, and compliance-aware architecture in healthcare applications. This platform is presented as a research prototype and is not a certified medical device.
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