Palaniappan Kavitha, Lin Elaine Yan Ting, Vogel Silke, Lim John C W
Centre of Regulatory Excellence, Duke-NUS Medical School, Singapore 169857, Singapore.
Healthcare (Basel). 2024 Aug 30;12(17):1730. doi: 10.3390/healthcare12171730.
Artificial Intelligence (AI) has shown remarkable potential to revolutionise healthcare by enhancing diagnostics, improving treatment outcomes, and streamlining administrative processes. In the global regulatory landscape, several countries are working on regulating AI in healthcare. There are five key regulatory issues that need to be addressed: (i) -measures to cover the "digital health footprints" left unknowingly by patients when they access AI in health services; (ii) -availability of safe and secure data and more open database sources for AI, algorithms, and datasets to ensure equity and prevent demographic bias; (iii) -mapping of the explainability and causability of the AI system; (iv) -whether this lies with the healthcare professional, healthcare organisation, or the personified AI algorithm; (v) -whether fundamental rights of people are met in an ethical manner. Policymakers may need to consider the entire life cycle of AI in healthcare services and the databases that were used for the training of the AI system, along with requirements for their risk assessments to be publicly accessible for effective regulatory oversight. AI services that enhance their functionality over time need to undergo repeated algorithmic impact assessment and must also demonstrate real-time performance. Harmonising regulatory frameworks at the international level would help to resolve cross-border issues of AI in healthcare services.
人工智能（AI）已展现出通过增强诊断、改善治疗效果和简化行政流程来彻底改变医疗保健的巨大潜力。在全球监管格局中，多个国家正在致力于对医疗保健领域的人工智能进行监管。有五个关键监管问题需要解决：（i）应对患者在使用医疗保健服务中的人工智能时无意中留下的“数字健康足迹”的措施；（ii）为人工智能、算法和数据集提供安全可靠的数据以及更开放的数据库来源，以确保公平性并防止人口统计学偏差；（iii）绘制人工智能系统的可解释性和因果关系；（iv）这是由医疗保健专业人员、医疗保健组织还是拟人化的人工智能算法负责；（v）人们的基本权利是否以符合道德的方式得到满足。政策制定者可能需要考虑医疗保健服务中人工智能的整个生命周期以及用于训练人工智能系统的数据库，以及其风险评估要求需公开可获取以进行有效的监管监督。随着时间推移功能不断增强的人工智能服务需要进行反复的算法影响评估，并且还必须展示实时性能。在国际层面协调监管框架将有助于解决医疗保健服务中人工智能跨境问题。
