目的:人工智能(AI)在改善皮肤科护理服务方面具有巨大潜力。基于AI的软件即医疗设备(SaMD)的最终用户(卫生专业人员和公众)需要相关的标签信息,以确保这些设备可以被适当地使用。目前,皮肤科AI-basedSaMD没有明确的最低标签要求。
方法:澳大利亚数字健康和皮肤病学专家小组通过改良的Delphi共识程序评估了最近文献综述中确定的基于AI的SaMD的常见标签建议。用9分的李克特量表表示10个项目的重要性,并进行了投票,以确定某些项目的具体特征。当超过75%的专家同意必须纳入信息时,就达成了共识。
结果:有强有力的共识支持将所有拟议项目纳入最低标签要求;使用说明,预期用户,训练和测试数据集,算法设计,图像处理技术,临床验证,性能指标,局限性,更新和不良事件。标签项目的几乎所有建议特征都得到认可,除了一些与性能度量相关的特征。此外,大家一致认为,统一的标签标准应适用于治疗用品管理局规定的所有人工智能类别和风险类别.
结论:这项研究为治疗用品管理局制定标签标准以保护患者提供了重要证据,卫生专业人员,消费者,工业,以及来自基于AI的皮肤病学SaMD的监管机构,这些机构目前没有提供关于它们是如何开发和测试的足够信息。
OBJECTIVE: Artificial intelligence (AI) holds remarkable potential to improve care delivery in dermatology. End users (health professionals and general public) of AI-based Software as Medical Devices (SaMD) require relevant labelling information to ensure that these devices can be used appropriately. Currently, there are no clear minimum
labelling requirements for dermatology AI-based SaMDs.
METHODS: Common labelling recommendations for AI-based SaMD identified in a recent literature review were evaluated by an Australian expert panel in digital health and dermatology via a modified Delphi
consensus process. A nine-point Likert scale was used to indicate importance of 10 items, and voting was conducted to determine the specific characteristics to include for some items.
Consensus was achieved when more than 75% of the experts agreed that inclusion of information was necessary.
RESULTS: There was robust
consensus supporting inclusion of all proposed items as minimum labelling requirements; indication for use, intended user, training and test data sets, algorithm design, image processing techniques, clinical validation, performance metrics, limitations, updates and adverse events. Nearly all suggested characteristics of the labelling items received endorsement, except for some characteristics related to performance metrics. Moreover, there was
consensus that uniform
labelling criteria should apply across all AI categories and risk classes set out by the Therapeutic Goods Administration.
CONCLUSIONS: This study provides critical evidence for setting labelling standards by the Therapeutic Goods Administration to safeguard patients, health professionals, consumers, industry, and regulatory bodies from AI-based dermatology SaMDs that do not currently provide adequate information about how they were developed and tested.