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骨科研究中人工智能实施实用指南 - 第7部分:医学人工智能系统的风险、局限性、安全性与验证

A practical guide to the implementation of AI in orthopaedic research-Part 7: Risks, limitations, safety and verification of medical AI systems.

作者信息

Winkler Philipp W, Zsidai Bálint, Hamrin Senorski Eric, Pruneski James A, Hirschmann Michael T, Ley Christophe, Tischer Thomas, Herbst Elmar, Pareek Ayoosh, Musahl Volker, Oeding Jacob F, Oettl Felix C, Longo Umile Giuseppe, Samuelsson Kristian, Feldt Robert

机构信息

Department for Orthopaedics and Traumatology Kepler University Hospital GmbH, Johannes Kepler University Linz Linz Austria.

Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden.

出版信息

J Exp Orthop. 2025 Apr 24;12(2):e70247. doi: 10.1002/jeo2.70247. eCollection 2025 Apr.

DOI:10.1002/jeo2.70247
PMID:40276496
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12019299/
Abstract

UNLABELLED

Artificial intelligence (AI) has been influencing healthcare and medical research for several years and will likely become indispensable in the near future. AI is intended to support healthcare professionals to make the healthcare system more efficient and ultimately improve patient outcomes. Despite the numerous benefits of AI systems, significant concerns remain. Errors in AI systems can pose serious risks to human health, underscoring the critical need for safety, as well as adherence to ethical and moral standards, before these technologies can be integrated into clinical practice. To address these challenges, the development, certification, and deployment of medical AI systems must adhere to strict and transparent regulations. The European Commission has already established a regulatory framework for AI systems by enacting the European Union Artificial Intelligence Act. This review article, part of an AI learning series, discusses key considerations for medical AI systems such as reliability, accuracy, trustworthiness, lawfulness and legal compliance, ethical and moral alignment, sustainability, and regulatory oversight.

LEVEL OF EVIDENCE

Level V.

摘要

未标注

人工智能(AI)多年来一直在影响医疗保健和医学研究,并且在不久的将来可能会变得不可或缺。人工智能旨在支持医疗保健专业人员,使医疗系统更高效,并最终改善患者的治疗效果。尽管人工智能系统有诸多好处,但仍存在重大问题。人工智能系统中的错误可能对人类健康构成严重风险,这凸显了在这些技术融入临床实践之前,确保安全以及遵守伦理和道德标准的迫切需求。为应对这些挑战,医疗人工智能系统的开发、认证和部署必须遵守严格且透明的法规。欧盟委员会已通过颁布《欧盟人工智能法案》,为人工智能系统建立了监管框架。这篇综述文章是人工智能学习系列的一部分,讨论了医疗人工智能系统的关键考量因素,如可靠性、准确性、可信度、合法性和法律合规性、伦理和道德一致性、可持续性以及监管监督。

证据级别

V级。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1b4/12019299/0b627c00a977/JEO2-12-e70247-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1b4/12019299/71f6ba5c76e8/JEO2-12-e70247-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1b4/12019299/0b627c00a977/JEO2-12-e70247-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1b4/12019299/71f6ba5c76e8/JEO2-12-e70247-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1b4/12019299/0b627c00a977/JEO2-12-e70247-g002.jpg

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2
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.TRIPOD+AI 声明:报告使用回归或机器学习方法的临床预测模型的更新指南。
BMJ. 2024 Apr 16;385:e078378. doi: 10.1136/bmj-2023-078378.
3
A practical guide to the implementation of AI in orthopaedic research - part 1: opportunities in clinical application and overcoming existing challenges.
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The world's week on AI safety: powerful computing efforts launched to boost research.全球人工智能安全周:启动强大计算工作以推动研究。
Nature. 2023 Nov;623(7986):229-230. doi: 10.1038/d41586-023-03472-x.
5
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