Delivering large scale digital clinical trials for artificial intelligence

该项目旨在通过为人工智能应用程序创建近乎实时的评估工具包，加快人工智能在医疗保健领域的部署、评估和调试。对于中小型企业来说，人工智能应用的临床试验成本可能过高，这使得它们难以证明其产品的安全性和有效性。为了解决这一问题，该项目有三个主要目标：确定适当的性能指标，以识别医疗保健中安全可靠的人工智能应用程序；在不中断临床用户工作流程的情况下，近乎实时地收集临床用户的反馈；在保持数据隐私的同时，大规模生成有效性证据。该项目将使用混合方法研究和隐私保护联合人工智能软件评估工具包来实现这些目标，一旦完成，将在中小企业、医疗保健提供者和专员的帮助下，用于大规模评估人工智能。

The project aims to speed up the deployment, evaluation, and commissioning of AI in healthcare by creating a near real-time evaluation toolkit for AI applications. The cost of clinical trials for AI applications can be prohibitively expensive for small and medium-sized businesses, making it difficult for them to prove the safety and efficacy of their products.To address this issue, the project has three main goals: to determine the appropriate performance metrics for identifying safe and trustworthy AI applications in healthcare, to gather feedback from clinical users in near real-time without interrupting their workflows, and to generate evidence of efficacy at a large scale while maintaining data privacy.The project will use mixed methods research and a privacy-preserving federated AI software evaluation toolkit to achieve these goals, and once completed, will be used to evaluate AI at a large scale with the help of SMEs, healthcare providers, and commissioners.