Prototype Learning to Create Refined Interpretable Digital Phenotypes from ECGs.

Abstract excerpt

Prototype-based neural networks offer interpretable predictions by comparing inputs to learned, representative signal patterns anchored in training data. While such models have shown promise in the classification of physiological data, it remains unclear whether their prototypes capture an underlying structure that aligns with broader clinical phenotypes.We use a prototype-based deep learning model trained for...

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