Medical AI products require certification before deployment in most jurisdictions. To date, no clear pathways for regulating medical AI exist. I present a methodological guide to the development of a regulatory package which will form part of a certification process. This approach is predicated on the translation between a statistical risk perspective, typical of medical device regulators, and a deep understanding of machine learning methodologies. This work of translation envisages the statistician as the key negotiator between medical device regulators and machine learning experts, allowing them to communicate more clearly, and thus lead to the development of standardised pathways for medical AI regulation.
翻译:在大多数司法管辖区,医疗自译自审产品在部署前需要认证。迄今为止,尚无明确的医疗自审监管途径。我为制定一揽子监管措施提供了方法指南,这将构成认证进程的一部分。这种方法的前提是从统计风险角度、医疗设备监管者的典型特征和对机器学习方法的深入理解之间翻译。翻译工作设想统计员作为医疗设备监管者和机器学习专家之间的主要谈判人,使他们能够进行更明确的沟通,从而导致制定医疗自审监管的标准路径。