PEACE: Private and Energy-Efficient Algorithm for Cardiac Evaluation on the EDGE using Modified Split Learning and Model Quantization
Author:
Affiliation:
1. Chair of Information Theory and Data Analytics
2. Chair of Integrated Digital Systems and Circuit Design RWTH Aachen University,Aachen,Germany,D-52074
Funder
Federal Ministry of Education and Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10330164/10330433/10330472.pdf?arnumber=10330472
Reference36 articles.
1. Mechanisms of cardiac arrhythmias
2. Optimizing Temporal Convolutional Network Inference on FPGA-Based Accelerators
3. Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL
4. Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review
5. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction
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