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

被引：4

作者：

Gong, Eun Jeong ^{[1
]}

Bang, Chang Seok ^{[1
]}

机构：

[1] Hallym Univ, Coll Med, Dept Internal Med, Sakju Ro 77, Chunchon 24253, Gangwon Do, South Korea

来源：

WORLD JOURNAL OF GASTROENTEROLOGY | 2024年 / 30卷 / 29期

关键词：

Crohn's disease; Ulcerative colitis; Inflammatory bowel disease; Chat generative pre-trained transformer; Large language model; Artificial intelligence;

D O I：

10.3748/wjg.v30.i29.3538

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

This letter evaluates the article by Gravina et al 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.

引用

页码：3538 / 3540

页数：4

共 4 条

[1] May ChatGPT be a tool producing medical information for common inflammatory bowel disease patients' questions? An evidence-controlled analysis [J].