Efficient and Private ECG Classification on the Edge Using a Modified Split Learning Mechanism

Author:

Ayad Ahmad1,Frei Marian1,Schmeink Anke1

Affiliation:

1. ISEK Teaching and Research Area RWTH Aachen University,Aachen,Germany,D-52074

Funder

Federal Ministry of Education and Research (BMBF, Germany)

Publisher

IEEE

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Smart Summary: A Distributed Medical Recommender System for Patients in the ICU Using Neural Networks;IEEE Access;2024

2. Detecting Data Poisoning in Split Learning Using Intraclass- Distance Inflated Loss;2023 IEEE Globecom Workshops (GC Wkshps);2023-12-04

3. PEACE: Private and Energy-Efficient Algorithm for Cardiac Evaluation on the EDGE using Modified Split Learning and Model Quantization;2023 14th International Conference on Information and Communication Systems (ICICS);2023-11-21

4. PSLF: Defending Against Label Leakage in Split Learning;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

5. An Efficient and Private ECG Classification System Using Split and Semi-Supervised Learning;IEEE Journal of Biomedical and Health Informatics;2023-09

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