AI can ID small vessel disease with 85% accuracy

Researchers at Imperial College London and the University of Edinburgh have developed machine learning software that detects small vessel disease (SVD)—which can ultimately cause stroke.

SVD, as reported by HealthImaging, is a common neurological disease that reduces blood flow to white matter connections in the brain, killing brain cells and possibly leading to stroke.

"The importance of our new method is that it allows for precise and automated measurement of the disease [SVD]," said lead author Paul Bentley, PhD, of Imperial College of London. "This also has applications for widespread diagnosis and monitoring of dementia, as well as for emergency decision-making in stroke.”

The researchers collected more than 1,000 CT scans of stroke patients from 70 different hospitals across the U.K. over a four-year period. Once the machine learning software identified SVD images, the researchers compared the AI results to those from a panel of experts who estimated SVD severity from CT scans alone—finding the software achieved 85 percent accuracy.

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As a senior news writer for TriMed, Subrata covers cardiology, clinical innovation and healthcare business. She has a master’s degree in communication management and 12 years of experience in journalism and public relations.

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