Alexander N. Olesen - Publications

Deep transfer learning for improving single-EEG arousal detection.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Published: October 06, 2020

Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the Polysomnogram.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Published: January 18, 2020

Automatic sleep stage classification with deep residual networks in a mixed-cohort setting.

Journal: Sleep

Published: January 06, 2020

Proteomic biomarkers of sleep apnea.

Journal: Sleep

Published: October 26, 2019

Automatic detection of cortical arousals in sleep and their contribution to daytime sleepiness.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology

Published: August 29, 2019

Design of a deep learning model for automatic scoring of periodic and non-periodic leg movements during sleep validated against multiple human experts.

Journal: Sleep medicine

Published: July 31, 2019

Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Published: November 17, 2018

A New Fully Automated Random-Forest Algorithm for Sleep Staging.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Published: November 17, 2018

Comparison of computerized methods for rapid eye movement sleep without atonia detection.

Journal: Sleep

Published: March 12, 2018

Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy.

Journal: Nature communications

Published: October 01, 2017

A comparative study of methods for automatic detection of rapid eye movement abnormal muscular activity in narcolepsy.

Journal: Sleep medicine

Published: June 24, 2017

A Noise-Assisted Data Analysis Method for Automatic EOG-Based Sleep Stage Classification Using Ensemble Learning.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Published: March 09, 2017