Artificial Intelligence Can Revolutionize Stroke Care
The Use of AI Could Lead to Faster, More Precise Interventions to Accelerate Life-Saving Treatment
Stroke remains the second leading cause of death worldwide, with many survivors facing life-altering disabilities. A new study by New York Medical College (NYMC) faculty and students, published in Intelligence-Based Medicine, reveals how integrating artificial intelligence (AI) in stroke detection could revolutionize stroke care by ensuring faster, more precise interventions.
“In acute stroke care, the timeless adage 'Time is brain' has never been more relevant,” explains Sonali Dadoo, SOM Class of 2025, one of the study’s authors. “Our research suggests that AI can quickly identify acute strokes on CT scans, acting as a critical tool to accelerate life-saving treatments.” Dadoo emphasizes that as technological innovations advance, it is imperative to harness these tools to support clinical expertise and provide the highest level of care.
According to the study, deep learning algorithms can analyze CT head and CT angiogram imaging to detect stroke patterns from large vessel occlusion to cerebral perfusion defects. AI applications in stroke care extend beyond detection, aiding in triage, measuring infarct volume, and predicting stroke burden—all essential for improving patient outcomes.
“AI’s ability to detect large vessel occlusions in real-time is critical,” says Dadoo. “As these technologies evolve, it will be crucial to assess its impact on health care efficiency, cost-effectiveness, and long-term clinical outcomes.”
NYMC authors on the study also include Elan Zebrowitz, M.D. ’24; Paige Brabant, SOM Class of 2025; Anaz Uddin, SOM Class of 2025; Esewi Aifuwa, SOM Class of 2025; Danielle Maraia, M.D. ’24; and Mill Etienne, M.D. ’02, M.P.H., vice chancellor for diversity and inclusion, associate dean for SOM student affairs, and professor of neurology and of medicine.
