Brain aneurysms detected using AI diagnostic tool

Built upon an algorithm called HeadXNet, the tool highlights areas in the brain that are likely to contain an aneurysm. During testing, it helped doctors correctly identify six more aneurysms per 100 scans that displayed the condition. According to the team, the AI also improved consensus among the clinicians that took part in the trial. The research is published in Jama Network Open.

"Search for an aneurysm is one of the most labour-intensive and critical tasks radiologists undertake," said Kristen Yeom, associate professor of radiology at Stanford and co-senior author of the paper. "Given inherent challenges of complex neurovascular anatomy and potential fatal outcome of a missed aneurysm, it prompted me to apply advances in computer science and vision to neuroimaging."

https://www.theengineer.co.uk/ai-medical-diagnostics/

To train the algorithm, Yeom worked with co-author Allison Park, a Stanford graduate student in statistics, and Christopher Chute, a graduate student in computer science. Together they outlined clinically significant aneurysms detectable on 611 computerised tomography (CT) angiogram head scans.