ConfSleepNet introduces a conflict-aware evidential aggregation method for multi-modal sleep stage classification using hybrid category structures per modality to produce reliable joint decisions with uncertainty.
IEEE Transactions on Biomedical Engineering , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
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Augmenting multimodal pediatric sleep embeddings with PHATE trajectories, persistent homology, movement descriptors, and EHR improves AUPRC and calibration for predicting desaturation, EEG arousal, hypopnea, and apnea.
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A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification
ConfSleepNet introduces a conflict-aware evidential aggregation method for multi-modal sleep stage classification using hybrid category structures per modality to produce reliable joint decisions with uncertainty.
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Uncovering Trajectory and Topological Signatures in Multimodal Pediatric Sleep Embeddings
Augmenting multimodal pediatric sleep embeddings with PHATE trajectories, persistent homology, movement descriptors, and EHR improves AUPRC and calibration for predicting desaturation, EEG arousal, hypopnea, and apnea.