A rule-based sleep staging method operationalizing AASM scoring rules achieves 60.5% agreement with human majority-vote consensus on 50 PSG recordings while providing epoch-level explanations.
Lorenzen, Elisabeth Heremans, Oliver Y
2 Pith papers cite this work. Polarity classification is still indexing.
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Randomly initialized Transformers act as adaptive sequence smoothers for sleep staging via a Random Attention Prior Kernel, with gains mainly from inductive bias rather than training.
citing papers explorer
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Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules
A rule-based sleep staging method operationalizing AASM scoring rules achieves 60.5% agreement with human majority-vote consensus on 50 PSG recordings while providing epoch-level explanations.
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Rethinking Random Transformers as Adaptive Sequence Smoothers for Sleep Staging
Randomly initialized Transformers act as adaptive sequence smoothers for sleep staging via a Random Attention Prior Kernel, with gains mainly from inductive bias rather than training.