Do not sleep on traditional machine learning: Simple and interpretable techniques are competitive to deep learning for sleep scoring
TL
TL;DR
It is shown that, for the sleep stage scoring task, the expressiveness of an engineered feature vector is on par with the internally learned representations of deep learning models, which opens the door to clinical adoption.
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