目的:这篇叙述性综述旨在概述危险,有争议的方面,以及人工智能(AI)在眼科和其他医疗相关领域的应用。
方法:我们对学术和灰色文献进行了长达十年的全面搜索(2013年1月至2023年5月),专注于人工智能在眼科和医疗保健领域的应用。此搜索包括关键的基于Web的学术数据库,非传统来源,以及对特定组织和机构的有针对性的搜索。我们审查并选择了与人工智能相关的文档,healthcare,伦理,和指导方针,旨在对伦理进行批判性分析,道德,以及人工智能在医疗保健中的法律含义。
结果:确定了六个主要问题,分析,并讨论。这些包括偏见和临床安全性,网络安全,健康数据和AI算法所有权,“黑匣子”问题,医疗责任,以及扩大医疗保健不平等的风险。
结论:解决这些问题的解决方案包括收集目标人群的高质量数据,纳入更强有力的安全措施,使用可解释的人工智能算法和集成方法,并使每个人都可以使用基于AI的解决方案。经过仔细的监督和监管,基于AI的系统可用于补充医生的决策并改善患者护理和结果。
OBJECTIVE: 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.
CONCLUSIONS: 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.