大型语言模型用于自动化临床试验匹配.
Ethan Layne1,2, Claire Olivas1,2, Jacob Hershenhouse1,2
1USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine.
Current opinion in urology
|March 21, 2025
概括
使用大语言模型 (LLM) 的生成人工智能 (GAI) 显示出与癌症临床试验匹配患者的前景. 虽然人工数据有效,但人类监督对于现实应用和患者安全至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 在瘤学中使用人工智能
- 临床试验管理 临床试验管理
背景情况:
- 生成型人工智能 (GAI) 和大型语言模型 (LLM) 在医学中越来越多地被使用.
- 患者与临床试验相匹配是GAI/LLM应用的一个关键领域.
- 本次审查重点关注LLM在临床试验匹配方面的当前能力.
研究的目的:
- 概述目前利用LLM进行临床试验匹配的现状.
- 评估LLM在将患者与瘤临床试验相匹配方面的表现.
主要方法:
- 对临床试验匹配中LLM绩效的最新研究的审查.
- 对LLM申请进行检查,将病人的病历与试验资格标准相匹配.
主要成果:
- 在将患者与瘤临床试验相匹配方面,LLM显示出有希望的结果,特别是在人工数据集方面.
- 目前的LLM系统需要人类监督才能准确安全地应用.
- 研究表明,潜在的好处包括改善患者接入和减少提供者的工作负担.
结论:
- 通过LLMs自动化临床试验匹配可以提高患者的访问,自主性和试验招生.
- 挑战包括患者潜在的"虚假希望",导航困难和需要人类监督.
- 进一步的研究对于确保LLM基于瘤学匹配的安全性和有效性至关重要,解决数据隐私和EMR/EHR集成问题.
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