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大语言模型在系统评价和荟萃分析制作中的潜在作用。

Potential Roles of Large Language Models in the Production of Systematic Reviews and Meta-Analyses.

机构信息

Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.

World Health Organization Collaboration Center for Guideline Implementation and Knowledge Translation, Lanzhou, China.

出版信息

J Med Internet Res. 2024 Jun 25;26:e56780. doi: 10.2196/56780.

Abstract

Large language models (LLMs) such as ChatGPT have become widely applied in the field of medical research. In the process of conducting systematic reviews, similar tools can be used to expedite various steps, including defining clinical questions, performing the literature search, document screening, information extraction, and language refinement, thereby conserving resources and enhancing efficiency. However, when using LLMs, attention should be paid to transparent reporting, distinguishing between genuine and false content, and avoiding academic misconduct. In this viewpoint, we highlight the potential roles of LLMs in the creation of systematic reviews and meta-analyses, elucidating their advantages, limitations, and future research directions, aiming to provide insights and guidance for authors planning systematic reviews and meta-analyses.

摘要

大型语言模型(LLMs)如 ChatGPT 已广泛应用于医学研究领域。在进行系统评价的过程中,类似的工具可用于加速各个步骤,包括定义临床问题、进行文献检索、文件筛选、信息提取和语言精炼,从而节约资源并提高效率。然而,在使用 LLM 时,应注意透明报告、区分真假内容并避免学术不端行为。在本观点中,我们强调了 LLM 在系统评价和荟萃分析创作中的潜在作用,阐明了它们的优势、局限性和未来研究方向,旨在为计划进行系统评价和荟萃分析的作者提供见解和指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff81/11234072/8f46a9d568d8/jmir_v26i1e56780_fig1.jpg

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