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 can enhance the accuracy and effectiveness of ECG-related diagnoses, especially for cardiac conditions where limited data is available on which to train. In a study published in the June 6 online issue of npj Digital Medicine, the team reported that its new deep learning model, known as HeartBEiT, forms a foundation upon which specialized diagnostic models can be created and outperformed convolutional neural networks (CNNs).