Detecting Electrocardiogram Arrhythmia Empowered With Weighted Federated Learning

Detecting Electrocardiogram Arrhythmia Empowered With Weighted Federated Learning

In this study, a weighted federated learning approach is proposed for electrocardiogram (ECG) arrhythmia classification. The proposed approach considers the heterogeneity of data distribution among multiple clients in federated learning settings. The weight of each client is dynamically adjusted acc...

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Bibliographic Details
Main Authors: Rizwana Naz Asif, Allah Ditta, Hani Alquhayz, Sagheer Abbas, Muhammad Adnan Khan, Taher M. Ghazal, Sang-Woong Lee
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Federated learning
MIT-BIH arrhythmia
electrocardiogram
client-side
server-side
Online Access:https://ieeexplore.ieee.org/document/10374338/

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