智能医疗的未来:利用大语言模型系统分析和讨论机器人在医疗保健领域的整合及其影响

Robotics Pub Date : 2024-07-23 DOI:10.3390/robotics13080112
Souren Pashangpour, G. Nejat
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引用次数: 0

摘要

随着人口老龄化和医疗保健专业人员的短缺,世界各地的医疗保健系统面临着巨大的需求,在医疗保健机器人中使用大型语言模型(LLMs)的可能性有助于解决这一问题。尽管 LLM 已被整合到医学中,为临床医生和患者提供帮助,但在临床环境中将 LLM 整合到医疗保健机器人中的问题尚未得到探讨。在这篇视角论文中,我们研究了机器人学和 LLM 的突破性发展,从而独特地确定了设计基于 LLM 的医疗专用机器人所需的系统要求,包括通过人机交互(HRI)进行多模式交流、语义推理和任务规划。此外,我们还讨论了这一新兴创新领域的伦理问题、公开挑战和潜在的未来研究方向。
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The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare
The potential use of large language models (LLMs) in healthcare robotics can help address the significant demand put on healthcare systems around the world with respect to an aging demographic and a shortage of healthcare professionals. Even though LLMs have already been integrated into medicine to assist both clinicians and patients, the integration of LLMs within healthcare robots has not yet been explored for clinical settings. In this perspective paper, we investigate the groundbreaking developments in robotics and LLMs to uniquely identify the needed system requirements for designing health-specific LLM-based robots in terms of multi-modal communication through human–robot interactions (HRIs), semantic reasoning, and task planning. Furthermore, we discuss the ethical issues, open challenges, and potential future research directions for this emerging innovative field.
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