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CESFL-ECG: communication-efficient split federated learning for patient-independent ECG classification

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
ECG Monitoring and Analysis

Abstract

Code, per-run results, tables and figures for the manuscript "Communication-efficient split federated learning for patient-independent ECG classification". CESFL-ECG quantizes the smashed data and cut-layer gradients of split federated learning to 4 bits with stochastic rounding and is evaluated on MIT-BIH (DS1/DS2, five-fold patient-wise cross-validation) and INCART (zero-shot external validation). The ECG databases are not included.

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