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New deep learning model lays the foundation for specialized diagnostic models

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.

Mount Sinai AI model allows for language-based ECG readings

The research, which builds on a training approach similar to that of ChatGPT, uses image-based modeling for ECG analysis – potentially enabling more effective heart function assessment and diagnosis of heart attacks and hypertrophic cardiomyopathy.

Mount Sinai Scientists Employ Novel Deep Learning Method to Analyze ECGs as Language

Mount Sinai Scientists Employ Novel Deep Learning Method to Analyze ECGs as Language
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