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Mount Sinai researchers have developed an AI model, HeartBEiT, for electrocardiogram (ECG) analysis that interprets ECGs as language. This approach can improve the accuracy and detail of ECG-related diagnoses, even for rare conditions with limited data. The model outperforms traditional convolutional neural networks (CNNs) and highlights specific ECG areas responsible for heart conditions.
