Large Language Model Integrated Healthcare Cyber-Physical Systems Architecture

TL;DR

This paper proposes integrating large language models into healthcare cyber-physical systems to improve data processing, real-time visualization, and decision-making, addressing current system limitations.

Contribution

It introduces a novel architecture that embeds LLMs into HCPS, enhancing efficiency and AI capabilities in healthcare applications.

Findings

Improved data processing efficiency

Enhanced real-time patient visualization

Better decision-making support

Abstract

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.