TRIPOD-LLM 声明:报告大型语言模型使用情况的目标指南

Jack Gallifant, Majid Afshar, Saleem Ameen, Yindalon Aphinyanaphongs, Shan Chen, Giovanni Cacciamani, Dina Demner-Fushman, Dmitriy Dligach, Roxana Daneshjou, Chrystinne Fernandes, Lasse Hyldig Hansen, Adam Landman, Liam G. McCoy, Timothy Miller, Amy Moreno, Nikolaj Munch, David Restrepo, Guergana Savova, Renato Umeton, Judy Wawira Gichoya, Gary S. Collins, Karel G. M. Moons, Leo A. Celi, Danielle S. Bitterman
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引用次数: 0

摘要

大型语言模型(LLM)正迅速被医疗保健领域所采用,因此需要标准化的报告指南。我们提出了 TRIPOD-LLM,它是 TRIPOD+AI 声明的扩展,旨在应对生物医学应用中 LLM 的独特挑战。TRIPOD-LLM 提供了一份包含 19 个主要项目和 50 个子项目的综合核对表,涵盖了从标题到讨论的关键方面。指南采用模块化格式,以适应各种 LLM 研究设计和任务,其中 14 个主要项目和 32 个子项目适用于所有类别。TRIPOD-LLM 是通过快速德尔菲程序和专家共识制定的,它强调透明度、人为监督和特定任务的绩效报告。我们还引入了一个交互式网站(https://tripod-llm.vercel.app/),方便用户填写指南和生成 PDF 文件以备提交。作为一份有生命力的文件,TRIPOD-LLM 将与该领域共同发展,旨在通过全面的报告提高医疗保健领域 LLM 研究的质量、可重复性和临床适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The TRIPOD-LLM Statement: A Targeted Guideline For Reporting Large Language Models Use
Large Language Models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present TRIPOD-LLM, an extension of the TRIPOD+AI statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion. The guidelines introduce a modular format accommodating various LLM research designs and tasks, with 14 main items and 32 subitems applicable across all categories. Developed through an expedited Delphi process and expert consensus, TRIPOD-LLM emphasizes transparency, human oversight, and task-specific performance reporting. We also introduce an interactive website (https://tripod-llm.vercel.app/) facilitating easy guideline completion and PDF generation for submission. As a living document, TRIPOD-LLM will evolve with the field, aiming to enhance the quality, reproducibility, and clinical applicability of LLM research in healthcare through comprehensive reporting.
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