电子健康助理AI聊天机器人使用大型语言模型通过安全的分散通信提供个性化答案
Iuliu Alexandru Pap1, Stefan Oniga1,2
1Department of Electric, Electronic and Computer Engineering, Technical University of Cluj-Napoca, North University Center of Baia Mare, 430083 Baia Mare, Romania.
Sensors (Basel, Switzerland)
|September 28, 2024
概括
本研究介绍了一种AI健康助理,它增强了电子健康系统,提供了自然语言的医疗信息访问,同时确保了患者的隐私. 该系统使用分散的协议来实现安全,可扩展的通信和本地处理的大型语言模型.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 分散式系统 分散式系统 分散式系统
背景情况:
- 现有的电子卫生系统需要改进用户交互.
- 对医疗数据进行自然语言查询是一个重大挑战.
- 患者隐私和数据安全在医疗保健中至关重要.
研究的目的:
- 实施一个与电子健康数据采集系统集成的AI健康助理.
- 为患者和工作人员提供自然语言查询医疗信息.
- 通过使用分散的协议来确保安全和私密的通信.
主要方法:
- 使用Matrix分散开放协议开发一个聊天式接口.
- 整合可互换的大型语言模型 (LLM) 进行响应生成.
- 对LLM与患者数据的互动实施受限访问控制.
主要成果:
- 成功实施了人工智能健康助理,补充了电子健康系统.
- 展示自然,安全和私密的医疗信息查询.
- 可扩展的系统架构,由矩阵协议的联邦性质促进.
结论:
- 人工智能健康助理为访问电子健康信息提供了一种新的方法.
- 该系统增强了患者和医务人员的用户体验.
- 使用去中心化的协议可以确保隐私,安全性和可扩展性.
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