Suppr超能文献

开发和使用人工智能模型的研究的综合报告指南及清单

Comprehensive reporting guidelines and checklist for studies developing and utilizing artificial intelligence models.

作者信息

Kwak Sang Gyu, Kim Jonghae

机构信息

Department of Medical Statistics, Daegu Catholic University School of Medicine, Daegu, Korea.

Department of Anesthesiology and Pain Medicine, Daegu Catholic University Medical Center, Daegu Catholic University School of Medicine, Daegu, Korea.

出版信息

Korean J Anesthesiol. 2025 Jun;78(3):199-214. doi: 10.4097/kja.25075. Epub 2025 Mar 26.

Abstract

BACKGROUND

The rapid advancement of artificial intelligence (AI) in healthcare necessitates comprehensive and standardized reporting guidelines to ensure transparency, reproducibility, and ethical applications in clinical research. Existing reporting standards are limited by their focus on specific study designs. We aimed to develop a comprehensive set of guidelines and a checklist for reporting studies that develop and utilize AI models in healthcare, covering all essential components of AI research regardless of the study design.

METHODS

Two experts in statistics from the Statistical Round of the Korean Journal of Anesthesiology developed these guidelines and checklist. The key elements essential for AI model reporting were identified and organized into structured sections, including study design, data preparation, model training and evaluation, ethical considerations, and clinical implementation. Iterative reviews and feedback from clinicians and researchers were used to finalize the guidelines and checklist.

RESULTS

These guidelines provide a detailed description of each item on the checklist, ensuring comprehensive reporting of AI model research. Full details regarding the AI model specifications and data-handling processes are provided.

CONCLUSIONS

These guidelines and checklist are meant to serve as valuable tools for researchers, addressing key aspects of AI reporting, and thereby supporting the reliability, accountability, and ethical use of AI in healthcare research.

摘要

背景

人工智能(AI)在医疗保健领域的迅速发展需要全面且标准化的报告指南,以确保临床研究中的透明度、可重复性和道德应用。现有的报告标准因侧重于特定研究设计而受到限制。我们旨在制定一套全面的指南和清单,用于报告在医疗保健中开发和使用AI模型的研究,涵盖AI研究的所有基本组成部分,而不考虑研究设计。

方法

《韩国麻醉学杂志统计专刊》的两位统计学专家制定了这些指南和清单。确定了AI模型报告的关键要素,并将其组织成结构化的部分,包括研究设计、数据准备、模型训练与评估、伦理考量和临床应用。通过临床医生和研究人员的反复审查和反馈来最终确定指南和清单。

结果

这些指南对清单上的每个项目都进行了详细描述,确保对AI模型研究进行全面报告。提供了有关AI模型规格和数据处理过程的完整详细信息。

结论

这些指南和清单旨在作为研究人员的宝贵工具,解决AI报告的关键方面,从而支持AI在医疗保健研究中的可靠性、可问责性和道德使用。

相似文献

6
Reporting guidelines for artificial intelligence in healthcare research.人工智能在医疗保健研究中的报告指南。
Clin Exp Ophthalmol. 2021 Jul;49(5):470-476. doi: 10.1111/ceo.13943. Epub 2021 May 25.
9
Artificial intelligence in hospital infection prevention: an integrative review.医院感染预防中的人工智能:一项综合综述。
Front Public Health. 2025 Apr 2;13:1547450. doi: 10.3389/fpubh.2025.1547450. eCollection 2025.

本文引用的文献

7
The Effect of Image Resolution on Deep Learning in Radiography.图像分辨率对放射成像深度学习的影响
Radiol Artif Intell. 2020 Jan 22;2(1):e190015. doi: 10.1148/ryai.2019190015. eCollection 2020 Jan.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验