Study Shows How Artificial Intelligence Helped Detect Acute Neurological Cases Earlier
This study, published in Nature Medicine, shows how Mount Sinai Health System researchers designed an automated deep learning neural network that can detect acute neurological diseases such as stroke, hemorrhage, and hydrocephalus within minutes, enabling earlier intervention that can preserve neurological function and improve patient outcomes. It is the first study to use artificial intelligence (AI) to identify acute neurological disease and thus demonstrate a direct clinical application of AI in a randomized controlled trial.
The Leonard I. Malis, MD / Corinne and Joseph Graber Professor of Neurosurgery
Chair of Neurosurgery for the Mount Sinai Health System
Clinical Instructor of Neurosurgery and Director, AISINAI, Mount Sinai Health System, and Chief Neurosurgery Resident (PGY- 7), Icahn School of Medicine at Mount Sinai