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掩面之下:人工智能在眼科学中的伦理、道德和法律影响的批判性视角。

Behind the mask: a critical perspective on the ethical, moral, and legal implications of AI in ophthalmology.

机构信息

Department of Medicine - Ophthalmology, University of Udine, Udine, Italy.

Istituto Europeo di Microchirurgia Oculare - IEMO, Udine, Italy.

出版信息

Graefes Arch Clin Exp Ophthalmol. 2024 Mar;262(3):975-982. doi: 10.1007/s00417-023-06245-4. Epub 2023 Sep 25.

Abstract

PURPOSE

This narrative review aims to provide an overview of the dangers, controversial aspects, and implications of artificial intelligence (AI) use in ophthalmology and other medical-related fields.

METHODS

We conducted a decade-long comprehensive search (January 2013-May 2023) of both academic and grey literature, focusing on the application of AI in ophthalmology and healthcare. This search included key web-based academic databases, non-traditional sources, and targeted searches of specific organizations and institutions. We reviewed and selected documents for relevance to AI, healthcare, ethics, and guidelines, aiming for a critical analysis of ethical, moral, and legal implications of AI in healthcare.

RESULTS

Six main issues were identified, analyzed, and discussed. These include bias and clinical safety, cybersecurity, health data and AI algorithm ownership, the "black-box" problem, medical liability, and the risk of widening inequality in healthcare.

CONCLUSION

Solutions to address these issues include collecting high-quality data of the target population, incorporating stronger security measures, using explainable AI algorithms and ensemble methods, and making AI-based solutions accessible to everyone. With careful oversight and regulation, AI-based systems can be used to supplement physician decision-making and improve patient care and outcomes.

摘要

目的

本叙述性综述旨在概述人工智能(AI)在眼科和其他医学相关领域中的应用所带来的危险、争议性问题和影响。

方法

我们对学术和灰色文献进行了长达十年的综合搜索(2013 年 1 月至 2023 年 5 月),重点关注 AI 在眼科和医疗保健中的应用。此次搜索包括基于网络的主要学术数据库、非传统来源以及针对特定组织和机构的定向搜索。我们对与 AI、医疗保健、伦理和指南相关的文献进行了回顾和选择,旨在对 AI 在医疗保健中的伦理、道德和法律影响进行批判性分析。

结果

确定、分析和讨论了六个主要问题。这些问题包括:偏倚和临床安全性、网络安全、健康数据和 AI 算法所有权、“黑箱”问题、医疗责任以及医疗保健中不平等加剧的风险。

结论

解决这些问题的方法包括收集目标人群的高质量数据、采用更强有力的安全措施、使用可解释的 AI 算法和集成方法,并使基于 AI 的解决方案能够为所有人所使用。通过仔细的监督和监管,可以利用基于 AI 的系统来辅助医生决策,改善患者的护理和治疗效果。

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本文引用的文献

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Artificial intelligence in retinal disease: clinical application, challenges, and future directions.
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Front Med (Lausanne). 2022 Oct 13;9:875242. doi: 10.3389/fmed.2022.875242. eCollection 2022.
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