论文标题
用于调节医疗产品的AI
OnRAMP for Regulating AI in Medical Products
论文作者
论文摘要
医疗人工智能（AI）涉及将机器学习算法应用于生物医学数据集，以改善医疗实践。在大多数司法管辖区部署之前，纳入医疗AI的产品需要认证。迄今为止，调节医学AI的明确途径仍在开发中。在正式途径的水平下方是开发医疗AI解决方案的实际实践。该观点提出了与生产监管软件包兼容开发指南的最佳实践指南，该方案不管正式的监管道路如何，都将构成认证过程的核心组成部分。该方法是基于统计风险的观点，是医疗设备调节器的典型特征，以及对机器学习方法的深刻理解。这些准则将使各方在开发共同的良好机器学习实践（GMLP）时更加清楚地进行交流，从而导致医疗AI产品和法规的增强。
Medical Artificial Intelligence (AI) involves the application of machine learning algorithms to biomedical datasets in order to improve medical practices. Products incorporating medical AI require certification before deployment in most jurisdictions. To date, clear pathways for regulating medical AI are still under development. Below the level of formal pathways lies the actual practice of developing a medical AI solution. This Perspective proposes best practice guidelines for development compatible with the production of a regulatory package which, regardless of the formal regulatory path, will form a core component of a certification process. The approach is predicated on a statistical risk perspective, typical of medical device regulators, and a deep understanding of machine learning methodologies. These guidelines will allow all parties to communicate more clearly in the development of a common Good Machine Learning Practice (GMLP), and thus lead to the enhanced development of both medical AI products and regulations.
