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医学中的大型语言模型:应用,挑战和未来方向

Erlan Yu¹, Xuehong Chu¹, Wanwan Zhang¹

¹Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.

International journal of medical sciences

|June 16, 2025

概括

大型语言模型 (LLM) 在医学上表现有前途,有助于临床实践,研究和教育. 诸如幻觉和伦理等挑战需要进一步的研究才能得到广泛采用.

科学领域:

人工智能在医学中的应用
自然语言处理自然语言处理.
医疗保健技术技术医疗保健技术

背景情况:

大型语言模型 (LLM),以GPT-4为例,在自然语言处理任务中迅速发展.
医学领域,其复杂的数据和流程,为LLM应用提供了重大机会.
法学士越来越多地融入临床实践,医学研究和教育.

研究的目的:

为医学LLM应用提供全面的概述.
识别和讨论与在医疗保健中实施LLM相关的挑战.
探索医学LLM发展和整合的未来方向.

主要方法:

在医学领域的LLMs最近的进展的文献综述.
对临床实践,研究和教育中当前应用的分析.
确定关键挑战,包括幻觉,可解释性和道德问题.

主要成果:

在各种医疗应用中,LLM展示了变革的潜力.
显著的挑战阻碍了医学LLM的广泛采用,包括准确性和伦理方面的考虑.
未来的研究应侧重于标准化评估,多式联运能力和跨学科合作.

结论:

在医学领域,LLM为医疗领域带来了巨大的好处,提高了效率和潜在的结果.
解决诸如幻觉和道德问题等挑战对于可靠的医学LLM部署至关重要.
持续的研究和合作对于充分实现LLMs在全球医疗保健转型中的潜力至关重要.

关键词:

人工智能的人工智能大型语言模型.医疗应用医学应用自然语言处理自然语言处理.

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