A newly developed artificial intelligence system from the University of Michigan can analyze brain MRIs and deliver a diagnosis in a matter of seconds. The model identified neurological conditions with 97.5% accuracy and was also able to assess how urgently patients needed medical care. Researchers say this first-of-its-kind technology has the potential to reshape how brain imaging is handled across health systems in the United States. The system was designed to notify the most appropriate sub-specialist, such as a stroke neurologist or neurosurgeon. Feedback becomes available immediately after a patient completes imaging. Each year, millions of MRI scans are performed worldwide, many of them focused on neurological disease. Researchers say the demand for these scans is growing faster than the availability of neuroradiology services. This imbalance has contributed to staffing shortages, diagnostic delays, and errors. Depending on where a patient receives a scan, results may take days or even longer to return. Researchers emphasize that the work is still in an early evaluation phase. Future research will focus on incorporating more detailed patient information and electronic medical record data to further improve diagnostic accuracy.
