Department of Electric, Electronic and Computer Engineering, Technical University of Cluj-Napoca, North University Center of Baia Mare, 430083 Baia Mare, Romania.
Department of IT Systems and Networks, Faculty of Informatics, University of Debrecen, 4032 Debrecen, Hungary.
Sensors (Basel). 2024 Sep 23;24(18):6140. doi: 10.3390/s24186140.
In this paper, we present the implementation of an artificial intelligence health assistant designed to complement a previously built eHealth data acquisition system for helping both patients and medical staff. The assistant allows users to query medical information in a smarter, more natural way, respecting patient privacy and using secure communications through a chat style interface based on the Matrix decentralized open protocol. Assistant responses are constructed locally by an interchangeable large language model (LLM) that can form rich and complete answers like most human medical staff would. Restricted access to patient information and other related resources is provided to the LLM through various methods for it to be able to respond correctly based on specific patient data. The Matrix protocol allows deployments to be run in an open federation; hence, the system can be easily scaled.
在本文中，我们介绍了人工智能健康助手的实现，该助手旨在补充之前构建的电子健康数据采集系统，以帮助患者和医务人员。助手允许用户以更智能、更自然的方式查询医疗信息，尊重患者隐私，并通过基于 Matrix 去中心化开放协议的聊天式界面使用安全通信。助手的响应由可互换的大型语言模型 (LLM) 本地构建，该模型可以像大多数人类医务人员一样形成丰富完整的答案。通过各种方法限制对患者信息和其他相关资源的访问，以便 LLM 能够根据特定患者数据正确响应。Matrix 协议允许在开放联盟中运行部署；因此，系统可以轻松扩展。
