95 citations · 105 across the 3 of their papers we have counts for
3 papers · 1 filter
Automatic sleep stage classification with deep residual networks in a mixed-cohort setting
Alexander Neergaard Olesen, Poul Jennum, Emmanuel Mignot +1
Study Objectives: Sleep stage scoring is performed manually by sleep experts and is prone to subjective interpretation of scoring rules with low intra- and interscorer reliability.…
Deep transfer learning for improving single-EEG arousal detection
Alexander Neergaard Olesen, Poul Jennum, Emmanuel Mignot +1
Datasets in sleep science present challenges for machine learning algorithms due to differences in recording setups across clinics. We investigate two deep transfer learning strate…
Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms
Alexander Neergaard Olesen, Poul Jennum, Paul Peppard +2
We have developed an automatic sleep stage classification algorithm based on deep residual neural networks and raw polysomnogram signals. Briefly, the raw data is passed through 50…