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评估大型语言模型在炎症性肠病患者信息中的作用。

Evaluating the role of large language models in inflammatory bowel disease patient information.

机构信息

Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Gangwon-do, South Korea.

出版信息

World J Gastroenterol. 2024 Aug 7;30(29):3538-3540. doi: 10.3748/wjg.v30.i29.3538.

DOI:10.3748/wjg.v30.i29.3538
PMID:39156498
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11326091/
Abstract

This letter evaluates the article by Gravina on ChatGPT's potential in providing medical information for inflammatory bowel disease patients. While promising, it highlights the need for advanced techniques like reasoning + action and retrieval-augmented generation to improve accuracy and reliability. Emphasizing that simple question and answer testing is insufficient, it calls for more nuanced evaluation methods to truly gauge large language models' capabilities in clinical applications.

摘要

这封信评估了 Gravina 关于 ChatGPT 在为炎症性肠病患者提供医疗信息方面的潜力的文章。虽然有前景,但它强调需要推理+行动和检索增强生成等先进技术来提高准确性和可靠性。强调简单的问答测试是不够的,需要更细致的评估方法来真正评估大型语言模型在临床应用中的能力。

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本文引用的文献

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May ChatGPT be a tool producing medical information for common inflammatory bowel disease patients' questions? An evidence-controlled analysis.ChatGPT 能否成为一种为常见炎症性肠病患者问题提供医疗信息的工具?一项基于证据的分析。
World J Gastroenterol. 2024 Jan 7;30(1):17-33. doi: 10.3748/wjg.v30.i1.17.
2
Application of Machine Learning Based on Structured Medical Data in Gastroenterology.基于结构化医学数据的机器学习在胃肠病学中的应用
Biomimetics (Basel). 2023 Oct 28;8(7):512. doi: 10.3390/biomimetics8070512.