Are you a client?
Sign in to view the full news archive.
A £1 million project is underway to test the safety and effectiveness of artificial intelligence in the Scottish NHS. Funded by Innovate UK, the scheme involves collaboration between NHS Greater Glasgow and Clyde, NHS Lothian, and AI evaluation company Aival, to create a validation framework for AI tools.
Aival’s independent evaluation platform will be used to assess AI systems for diagnosing head trauma and lung cancer, aiming to improve care for patients and support NHS staff. The platform allows hospitals to verify AI performance using anonymised patient data and provides ongoing monitoring once the software is deployed.
The project will also test the Aival platform’s ability to monitor long-term AI performance, addressing concerns about ‘drift’—the decline in software accuracy over time due to changes in patient populations, disease trends, or equipment updates.
Dr Mark Hall, consultant radiologist at NHS Greater Glasgow and Clyde, said: "Post-deployment surveillance monitoring is a critical yet often overlooked aspect of patient care, especially in radiology, where early detection of disease progression can make all the difference. Despite its importance, there are currently no standardised guidelines. AI-powered monitoring software bridges this gap by providing a structured approach”
One of the challenges addressed by the project is the lengthy testing process for AI. Currently, it can take more than nine months to evaluate a single product, and there are more than 200 AI options available for some hospital departments. This has limited the rollout of AI solutions in clinical settings. The project will compare six commercial AI products used in stroke and lung cancer triage, including tools developed by InferVision, Annalise-AI, and Qure.AI.
AI has tremendous potential to improve patient care in healthcare, and we have already seen it applied in numerous use cases from taking patient notes to aiding consultations and suggesting treatment diagnosis. The key barrier, as with the application of AI in any heavily regulated industry, is trust and confidence that the systems will behave as expected and are safe to use. Both are key aspects this project will seek to test and which may well help establish important benchmarks for other healthcare organisations.
Posted by: Simon Baxter at 09:55
Tags:
healthcare