Suppr超能文献

人工智能聊天机器人在临床检验医学中的应用:基础与趋势

AI Chatbots in Clinical Laboratory Medicine: Foundations and Trends.

机构信息

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, United States.

Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.

出版信息

Clin Chem. 2023 Nov 2;69(11):1238-1246. doi: 10.1093/clinchem/hvad106.

Abstract

BACKGROUND

Artificial intelligence (AI) conversational agents, or chatbots, are computer programs designed to simulate human conversations using natural language processing. They offer diverse functions and applications across an expanding range of healthcare domains. However, their roles in laboratory medicine remain unclear, as their accuracy, repeatability, and ability to interpret complex laboratory data have yet to be rigorously evaluated.

CONTENT

This review provides an overview of the history of chatbots, two major chatbot development approaches, and their respective advantages and limitations. We discuss the capabilities and potential applications of chatbots in healthcare, focusing on the laboratory medicine field. Recent evaluations of chatbot performance are presented, with a special emphasis on large language models such as the Chat Generative Pre-trained Transformer in response to laboratory medicine questions across different categories, such as medical knowledge, laboratory operations, regulations, and interpretation of laboratory results as related to clinical context. We analyze the causes of chatbots' limitations and suggest research directions for developing more accurate, reliable, and manageable chatbots for applications in laboratory medicine.

SUMMARY

Chatbots, which are rapidly evolving AI applications, hold tremendous potential to improve medical education, provide timely responses to clinical inquiries concerning laboratory tests, assist in interpreting laboratory results, and facilitate communication among patients, physicians, and laboratorians. Nevertheless, users should be vigilant of existing chatbots' limitations, such as misinformation, inconsistencies, and lack of human-like reasoning abilities. To be effectively used in laboratory medicine, chatbots must undergo extensive training on rigorously validated medical knowledge and be thoroughly evaluated against standard clinical practice.

摘要

背景

人工智能(AI)对话代理,即聊天机器人,是设计用来使用自然语言处理模拟人类对话的计算机程序。它们在不断扩大的医疗保健领域提供了各种功能和应用。然而,它们在实验室医学中的作用尚不清楚,因为其准确性、可重复性以及解释复杂实验室数据的能力尚未经过严格评估。

内容

本文综述了聊天机器人的历史、两种主要的聊天机器人开发方法,以及它们各自的优缺点。我们讨论了聊天机器人在医疗保健中的能力和潜在应用,重点关注实验室医学领域。介绍了最近对聊天机器人性能的评估,特别强调了大型语言模型(如 Chat Generative Pre-trained Transformer)对不同类别实验室医学问题的响应能力,例如医学知识、实验室操作、法规以及与临床背景相关的实验室结果解释。我们分析了聊天机器人局限性的原因,并提出了开发更准确、可靠和易于管理的聊天机器人以应用于实验室医学的研究方向。

总结

作为快速发展的人工智能应用,聊天机器人具有极大的潜力,可以改善医学教育,及时响应与实验室测试相关的临床询问,协助解读实验室结果,并促进患者、医生和实验室人员之间的沟通。然而,用户应警惕现有聊天机器人的局限性,例如错误信息、不一致和缺乏类人推理能力。要在实验室医学中有效应用,聊天机器人必须经过严格验证的医学知识的广泛培训,并根据标准临床实践进行彻底评估。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验