Mount Sinai Researchers Use New Deep Learning Approach To Enable Analysis Of Electrocardiograms As Language

Mount Sinai researchers have developed an innovative artificial intelligence (AI) model for electrocardiogram (ECG) analysis that allows for the interpretation of ECGs as language. This approach, known as HeartBEiT, can enhance the accuracy and effectiveness of ECG-related diagnoses, especially for cardiac conditions where limited data is available on which to train. The team reported that HeartBEiT models created using their model surpassed established methods for ECG analysis, and can perform as well as, if not better than, these methods using a tenth of the data.