Why the study?
Edge inference faces constrained computing resources, challenging the deployment of heavy deep learning models for real-time ECG-based cardiac abnormality measurements.
Comparison
Lightweight student model vs heavy teacher model
Design
Model development and validation study
Authors
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Knowledge distillation may enable real-time ECG analysis on edge devices; leaves open prospective clinical validation before practice change.
A robust knowledge distillation methodology enables ultra-efficient and secure deep learning for real-time ECG-based cardiac abnormality detection on edge devices.
Wong et al. (2023) studied this question.
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