特发性肺纤维化大型语言模型生成医学信息评估表1

该数据集表格评估ChatGPT-4与Gemini 1.5 Pro生成的IPF医学信息质量、可靠性、可读性及与临床指南一致性。

NIAID Data Ecosystem
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表格idiopathic pulmonary fibrosisartificial intelligencenatural language processingmachine learninglarge language modelshealth information systemsquality of health careclinical decision-making
Table 1_Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.docx

基本信息

模态
表格
大小
0.000022061 GB
许可
CC BY 4.0
创建/更新时间
2026-10-17
版本
v1

资源简介

特发性肺纤维化大型语言模型生成医学信息评估表1

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 22.06 KB,主题涵盖 idiopathic pulmonary fibrosis、artificial intelligence、natural language processing、machine learning、large language models,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Table 1_Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.docx》。配套论文《The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis》发表于 Therapeutic Advances in Respiratory Disease(2024),DOI:10.1177/17534666241282538。源站首次发布:2025-09-24。

【数据内容】

源站原始描述:BackgroundIdiopathic Pulmonary Fibrosis (IPF) information from AI-powered large language models (LLMs) like ChatGPT-4 and Gemini 1.5 Pro is unexplored for quality, reliability, readability, and concordance with clinical guidelines. Research questionWhat is the quality, reliability, readability, and concordance to clinical guidelines of LLMs in medical and clinically IPF-related content? Study design and methodsChatGPT-4 and Gemini 1.5 Pro responses to 23 ATS/ERS/JRS/ALAT IPF guidelines questions…

【数据结构与技术规格】

文件数 1 个,合计 22.06 KB。Table 1_Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,22.06 KB。数据集 DOI:10.3389/frai.2025.1618378.s002。

【主题与分类】

源站学科分类:Knowledge Representation and Machine Learning。主题标签:idiopathic pulmonary fibrosis、artificial intelligence、natural language processing、machine learning、large language models、health information systems、quality of health care、clinical decision-making。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://frontiersin.figshare.com/articles/dataset/Table_1_Evaluation_of_large_language_model-generated_medical_information_on_idiopathic_pulmonary_fibrosis_docx/30194872

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Cherrez-Ojeda, Iván; Frye, Björn Christian; Hoheisel, Andreas; Cortes-Telles, Arturo; Robles-Velasco, Karla; Mateos-Toledo, Heidegger N.; et al. (2025). Table 1_Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.docx. Frontiers. Dataset

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使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "Table 1_Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.docx" "https://ndownloader.figshare.com/files/58186222"

文件清单

  • Table 1_Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.docx(22.06 KB)

文件总体积 22.06 KB(源站 API 实测)。

数据说明

BackgroundIdiopathic Pulmonary Fibrosis (IPF) information from AI-powered large language models (LLMs) like ChatGPT-4 and Gemini 1.5 Pro is unexplored for quality, reliability, readability, and concordance with clinical guidelines.
Research questionWhat is the quality, reliability, readability, and concordance to clinical guidelines of LLMs in medical and clinically IPF-related content?
Study design and methodsChatGPT-4 and Gemini 1.5 Pro responses to 23 ATS/ERS/JRS/ALAT IPF guidelines questions were compared. Six independent raters evaluated responses for quality (DISCERN), reliability (JAMA Benchmark Criteria), readability (Flesch–Kincaid), and guideline concordance (0–4). Descriptive analysis, Intraclass Correlation Coefficient, Wilcoxon signed-rank test, and effect sizes ® were calculated. Statistical significance was set at p According to JAMA Benchmark, ChatGPT-4 and Gemini 1.5 Pro provided partially reliable responses; however, readability evaluations showed that both models were difficult to understand. The Gemini 1.5 Pro provided significantly better treatment information (DISCERN score: 56 versus 43, p Both models gave useful medical insights, but their reliability is limited. Gemini 1.5 Pro gave greater quality information than ChatGPT-4 and was more compliant with worldwide IPF guidelines. Readability analyses found that AI-generated medical information was difficult to understand, stressing the need to refine it.
What is already known on this topicRecent advancements in AI, especially large language models (LLMs) powered by natural language processing (NLP), have revolutionized the way medical information is retrieved and utilized.
What this study addsThis study highlights the potential and limitations of ChatGPT-4 and Gemini 1.5 Pro in generating medical information on IPF. They provided partially reliable information in their responses; however, Gemini 1.5 Pro demonstrated superior quality in treatment-related content and greater concordance with clinical guidelines. Nevertheless, neither model provided answers in full concordance with established clinical guidelines, and their readability remained a major challenge.
How this study might affect

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/frai.2025.1618378.s002(source: https://frontiersin.figshare.com/articles/dataset/Table_1_Evaluation_of_large_language_model-generated_medical_information_on_idiopathic_pulmonary_fibrosis_docx/30194872)。

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