Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; University of Cambridge School of Clinical Medicine, Cambridge, UK; Oxford University Clinical Academic Graduate School, University of Oxford, Oxford, UK.
Cell Rep Med. 2023 Oct 17;4(10):101230. doi: 10.1016/j.xcrm.2023.101230.
Current and future healthcare professionals are generally not trained to cope with the proliferation of artificial intelligence (AI) technology in healthcare. To design a curriculum that caters to variable baseline knowledge and skills, clinicians may be conceptualized as "consumers", "translators", or "developers". The changes required of medical education because of AI innovation are linked to those brought about by evidence-based medicine (EBM). We outline a core curriculum for AI education of future consumers, translators, and developers, emphasizing the links between AI and EBM, with suggestions for how teaching may be integrated into existing curricula. We consider the key barriers to implementation of AI in the medical curriculum: time, resources, variable interest, and knowledge retention. By improving AI literacy rates and fostering a translator- and developer-enriched workforce, innovation may be accelerated for the benefit of patients and practitioners.
当前和未来的医疗保健专业人员通常没有接受过应对医疗保健领域人工智能 (AI) 技术激增的培训。为了设计一个满足不同基础知识和技能水平的课程，临床医生可以被视为“消费者”、“翻译者”或“开发者”。由于人工智能创新而对医学教育提出的要求与循证医学 (EBM) 带来的要求相关。我们概述了未来消费者、翻译者和开发者的人工智能教育核心课程，强调了人工智能和 EBM 之间的联系，并就如何将教学纳入现有课程提出了建议。我们考虑了在医学课程中实施人工智能的关键障碍：时间、资源、兴趣变化和知识保留。通过提高人工智能素养率并培养翻译者和开发者丰富的劳动力，创新可能会加速，使患者和从业者受益。
