Computing, Health, and Safety: Exploring the Potential of Federated Learning in Cardiac Arrhythmia Detection

• Arthur N. F. Martins da Costa UFOP
• Pedro Silva UFOP

DOI: https://doi.org/10.5753/ercas.2024.238587

Abstract

This article assesses the use of federated learning in the context of cardiac arrhythmia detection. A traditional Deep Learning approach was compared against a federated one, and it was observed that the federated approach was able to maintain predictive performance and training time similar to the original proposal while ensuring the security and privacy of data.

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