Developing valuable use cases to accelerate the adoption of AI

The NHS understood that a dedicated AI Lab was critical to adopting cutting-edge technologies across health and care services but they needed support to set this up. Two key challenges were identified in the discovery phase – no infrastructure to provide high-quality datasets to support model development, and no clear process for evaluating model performance and safety for clinical use.

Along with the NHSX and a consortium of academic research groups, including Royal Surrey NHS Foundation and the British Society of Thoracic Imaging, we designed and put to the test two new case studies to showcase the AI lab’s capabilities. One created the UK’s first centralised chest imaging database to help support the development of third-party tools, which AI developers can use to better train their models and improve performance. The second was designing and implementing a validation process for machine-learning models which takes companies through a rigorous monitoring phase to build up evidence for regulatory approvals and ensures that models are safe and effective for use on patients.

A novel approach to the adoption and performance of AI diagnostic technologies, brings benefits to patients and saves time for clinicians, assuring they are safe before they are rolled out for wider use. Our work will help ensure future AI tools are always adopted safely. Outside of the NHS, our validation process has helped guide the use of AI in medical diagnosis and inform new approaches to the international governance of AI in healthcare.