Artificial Intelligence Rivals Experts in Diagnosing Brain Bleeds

A deep learning algorithm can accurately detect acute intracranial hemorrhage (ICH) on head CT on par with highly trained neuroradiologists, in some cases identifying subtle abnormalities overlooked by the radiologists, new research shows. Only a "handful" of artificial intelligence (AI) applications in medical image interpretation have achieved this level of accuracy, Esther Yuh, PhD, of the University of California, San Francisco (UCSF), told Medscape Medical News. The study was supported by the California Initiative to Advance Precision Medicine and was published online October 21 in the Proceedings of the National Academy of Sciences. Head CT is the "workhorse" medical imaging modality for diagnosing neurologic emergencies, such as acute traumatic brain injury, stroke, and aneurysmal hemorrhage, the investigators note. "However, these gray scale images are limited by low signal-to-noise, poor contrast, and a high incidence of image artifacts. A unique challenge is to identify tiny subtle abnormalities in a large 3D volume with near-perfect sensitivity," they write.