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Doctors could soon get some help from an artificial intelligence tool when diagnosing brain aneurysms – bulges in blood vessels in the brain that can leak or burst open, potentially leading to stroke, brain damage or death.
The AI tool, developed by researchers at Stanford University and detailed in a paper publishedJune 7 in JAMA Network Open, highlights areas of a brain scan that are likely to contain an aneurysm.
“There’s been a lot of concern about how machine learning will actually work within the medical field,” said Allison Park, a Stanford graduate student in statistics and co-lead author of the paper. “This research is an example of how humans stay involved in the diagnostic process, aided by an artificial intelligence tool.”
This tool, which is built around an algorithm called HeadXNet, improved clinicians’ ability to correctly identify aneurysms at a level equivalent to finding six more aneurysms in 100 scans that contain aneurysms. It also improved consensus among the interpreting clinicians. While the success of HeadXNet in these experiments is promising, the team of researchers – who have expertise in machine learning, radiology and neurosurgery – cautions that further investigation is needed to evaluate generalizability of the AI tool prior to real-time clinical deployment given differences in scanner hardware and imaging protocols across different hospital centers. The researchers plan to address such problems through multi-center collaboration.