Researchers from New York City-based Mount Sinai have developed an AI algorithm to help physicians identify patients with hypertrophic cardiomyopathy by assigning a numeric probability risk assessment.
The algorithm has received FDA approval for the detection of HCM on an electrocardiogram, according to an April 22 news release shared with Becker’s.
“This is an important step forward in translating novel deep-learning algorithms into clinical practice,” Joshua Lampert, MD, director of machine learning at Mount Sinai Fuster Heart Hospital, said in the release. “Clinicians can improve their clinical workflows by ensuring the highest-risk patients are identified at the top of their clinical work list using a sorting tool.”
The researchers plan to further study the algorithm at health systems across the country.
At the Becker's 23rd Annual Spine, Orthopedic and Pain Management-Driven ASC + The Future of Spine Conference, taking place June 11-13 in Chicago, spine surgeons, orthopedic leaders and ASC executives will come together to explore minimally invasive techniques, ASC growth strategies and innovations shaping the future of outpatient spine care. Apply for complimentary registration now.
