Artificial Intelligence Imaging Collaboration Could Speed Up Triage of Covid-Suspected Cases

Three-minute Chest X-ray test using AI producing encouraging results

An arti cial Intelligence (AI) programme created by Bering Limited and a study conducted by iCAIRD, Scotland’s Industrial Centre for AI Research in Digital Diagnostics, has yielded promising results. To speed up Covid-19 diagnosis in patients who presented respiratory symptoms in hospital Emergency Departments (ED), chest X-rays have been used in a stimulated clinical test setting.

The iCAIRD studyi, funded by Innovate UK, was in partnership with NHS Greater Glasgow and Clyde, using Canon Medical Research Europe’s Safe Haven Arti cial Intelligence Platform (SHAIP), as well as datasets from the Glasgow Safe Haven. The study used a new AI algorithm giving an accurate Covid-19 result in a test environment in under three minutes with performance on par with four certi ed radiologists.

“This is another welcome development demonstrating the potential for AI to support clinicians ensuring patients are getting the highest quality and most-relevant treatment,” states Prof David Lowe, Joint Clinical Lead of the West of Scotland Innovation Hub and an Emergency Medicine Consultant at Queen Elizabeth University Hospital. “Through testing in a safe environment, we have been able to see that this algorithm can identify Covid-19 on Chest X-rays that were routinely taken during initial clinical assessment. This could not just help with the treatment of patients but may also speed up the process of isolating infected patients.”

Dr Mark Hall, Radiology Consultant at NHS Greater Glasgow & Clyde added, “We continue to see the positive potential impact AI could have on radiology, from reducing waiting times to improving accuracy and reducing pressures on sta . Ongoing research highlights the importance of using developments in AI to enhance diagnosis and treatment. The level of accuracy may allow consultants to make even more informed decisions as we have a greater pool of data to use. There can often be a misconception that AI input will mean the patients gets less time with doctors, but this is not the case. Technology like this may help to speed up processing high numbers of similar cases, while retaining accuracy, allowing for more time with patients and more complex cases.”

“Covid-19 along with many chronic diseases continually put pressure on our UK health services. Research and development into how we can speed-up diagnostic imaging is therefore incredibly important,” states Mark Hitchman, Managing Director of Canon Medical Systems UK. “There are also broader bene ts of having AI research situated in the UK via our sister company Canon Medical Research Europe. It means that the AI algorithms developed using the Safe Haven Arti cial Intelligence Platform are speci c in terms of demographics, meaning more readiness for UK patient population deployment.”

The Canon Medical Research Europe AI Centre of Excellence includes a team of data sciences, clinical analysts and software engineers based in Edinburgh who collaborate with the universities of Glasgow and Aberdeen and NHS hospitals including Queen Elizabeth University Hospital Glasgow and Aberdeen Royal In rmary. The team is developing a set of tools to help clinicians to create novel AI solutions using UK patient data for machine learning, together with infrastructure for data scientists to develop, train and validate algorithms without patient data ever leaving the hospital environment.