基于大语言模型的医疗智能助手应用研究进展

Research Progress on the Application of Large Language Model-based Intelligent Medical Assistants

  • 摘要: 以ChatGPT为代表的大语言模型因其具有强大的理解和生成人类语言的能力而备受关注, 在不同医疗任务中使用大语言模型的研究呈现出蓬勃发展趋势。本综述旨在概述大语言模型在临床中的应用进展, 重点关注医疗智能助手的主要任务, 包括其面临的机遇和挑战。在技术层面, 文中详尽阐述了现有医学大语言模型的结构及其训练过程, 并总结了将大语言模型应用至医疗领域的通用技术步骤; 在应用层面, 从面向医护人员和面向患者两方面介绍医疗智能助手的主要任务, 并比较了不同大语言模型在各种医疗任务中的表现, 以展示大语言模型在医学应用中的独特优势及其局限性。

     

    Abstract: Large language models (LLMs), represented by ChatGPT, have garnered significant attention due to their powerful capabilities in understanding and generating human language. Research on the application of LLMs across various medical tasks has shown a vigorous development trend. This review aims to outline the development and clinical applications of LLMs, with a focus on the primary tasks of medical intelligent assistants, including their associated opportunities and challenges. At the technical level, we provide a detailed explanation of the architecture and training processes of existing medical LLMs, and summarize the general technical steps for adapting large models to the healthcare domain. At the application level, we introduce the main tasks of medical intelligent assistants from both healthcare provider- and patient-oriented perspectives, andcompare the performance of different LLMs across various medical tasks to illustrate their unique advantages and limitations in medical applications.

     

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