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探索大型语言模型在黑色素瘤中的作用:系统性审查

Mor Zarfati¹, Girish N Nadkarni², Benjamin S Glicksberg²

¹Department of Internal Medicine, Soroka University Medical Center, Beer-Sheva 84101, Israel.

Journal of clinical medicine

|December 17, 2024

概括

大型语言模型 (LLM) 在黑色素瘤护理中显示出对患者教育和诊断的希望,但需要进一步验证临床管理. 目前的应用需要改进,以确保在不同患者群体和皮肤类型中确保准确性和通用性.

科学领域:

皮肤病学皮肤病学
人工智能的人工智能
医疗信息学医疗信息学

背景情况:

大型语言模型 (LLM) 越来越多地被用于医疗保健应用.
黑色素瘤护理提出了独特的挑战,需要准确和可访问的信息.

研究的目的:

系统地审查LLM在黑色素瘤护理中的应用,益处和挑战.
评估LLM在患者教育,诊断和黑色素瘤临床管理方面的表现.

主要方法:

在PubMed和Scopus进行系统的文献搜索,截至2024年7月.
遵守PRISMA指南和使用修改后的QUADAS-2进行偏差风险评估.
包括九项研究,按应用领域分类.

主要成果:

在患者教育方面,LLM表现出很高的准确性,但往往超过可读性指南.
多模式LLM显示了黑色素瘤的诊断潜力,但准确性是可变的.
LLM提供初步的管理咨询,但缺乏个性化决策的深度.

结论:

LLM,特别是多式变种,有可能提高黑色素瘤护理.
目前的LLM应用程序需要进一步验证和完善以供临床使用.
未来的研究应该专注于微调LLM与皮肤病学数据和专家知识.

关键词:

人工智能的人工智能是人工智能.大型语言模型.黑色素瘤是一种黑色素瘤.

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