BiFedKD improves ECG classification accuracy by 3.52% and Macro-F1 by 9.93% on MIT-BIH while cutting communication overhead 40% and computation cost 71.7% versus baseline federated methods.
Internet of medical things: A systematic review,
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QQMR applies Q-learning with priority queuing and fuzzy C-means clustering to select multipath routes in IoMT body area networks, raising packet delivery while cutting delay, overhead, and energy use.
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BiFedKD: Bidirectional Federated Knowledge Distillation Framework for Non-IID and Long-Tailed ECG Monitoring
BiFedKD improves ECG classification accuracy by 3.52% and Macro-F1 by 9.93% on MIT-BIH while cutting communication overhead 40% and computation cost 71.7% versus baseline federated methods.
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A Q-learning-based QoS-aware multipath routing protocol in IoMT-based wireless body area network
QQMR applies Q-learning with priority queuing and fuzzy C-means clustering to select multipath routes in IoMT body area networks, raising packet delivery while cutting delay, overhead, and energy use.