Demographic-stratified fine-tuning of a convolutional recurrent sleep staging model improves Cohen's kappa by 0.9-12.9% over a single population-agnostic baseline on 100 clinical PSG recordings.
Addressing wearable sleep tracking inequity: A new dataset and novel methods for a population with sleep disorders,
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Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography
Demographic-stratified fine-tuning of a convolutional recurrent sleep staging model improves Cohen's kappa by 0.9-12.9% over a single population-agnostic baseline on 100 clinical PSG recordings.