集成大语言模型的医疗信息物理系统架构
Large Language Model Integrated Healthcare Cyber-Physical Systems Architecture
AI总结：
针对医疗信息物理系统存在的数据录入慢、缺实时处理等问题，提出集成大语言模型的创新架构，通过在多层级引入LLM提升医疗系统效率与决策能力。
摘要：
信息物理系统已成为现代医疗行业的核心组成部分。医疗信息物理系统（HCPS）融合物理组件与网络组件，助力医疗行业发展。尽管HCPS优势众多，但仍存在数据录入流程冗长、缺乏实时处理能力、患者实时可视化效果有限等缺陷。为解决这些问题，本文提出一种创新方法：集成大语言模型（LLM）以提升医疗系统效率。通过在HCPS的不同层级引入LLM，系统可借助先进AI能力改善患者预后、优化数据处理并强化决策支持。
英文摘要：
Cyber-physical systems have become an essential part of the modern healthcare industry. The healthcare cyber-physical systems (HCPS) combine physical and cyber components to improve the healthcare industry. While HCPS has many advantages, it also has some drawbacks, such as a lengthy data entry process, a lack of real-time processing, and limited real-time patient visualization. To overcome these issues, this paper represents an innovative approach to integrating large language model (LLM) to enhance the efficiency of the healthcare system. By incorporating LLM at various layers, HCPS can leverage advanced AI capabilities to improve patient outcomes, advance data processing, and enhance decision-making.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
