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Valentin Thorey

Showing results (1-10 of 8) with videos related to

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IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|July 21, 2021
RobustSleepNet: Transfer Learning for Automated Sleep Staging at ScaleAntoine Guillot, Valentin Thorey
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|August 4, 2020
Dreem Open Datasets: Multi-Scored Sleep Datasets to Compare Human and Automated Sleep StagingAntoine Guillot, Fabien Sauvet, Emmanuel H During, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
AI vs Humans for the diagnosis of sleep apneaValentin Thorey, Albert Bou Hernandez, Pierrick J Arnal, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the PolysomnogramAlexander Neergaard Olesen, Stanislas Chambon, Valentin Thorey, et al.
Frontiers in Human Neuroscience|March 24, 2018
Performance of an Ambulatory Dry-EEG Device for Auditory Closed-Loop Stimulation of Sleep Slow Oscillations in the Home EnvironmentEden Debellemaniere, Stanislas Chambon, Clemence Pinaud, et al.
Sleep|May 21, 2020
The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep stagingPierrick J Arnal, Valentin Thorey, Eden Debellemaniere, et al.
Obstetrics and Gynecology|August 7, 2025
Artificial Intelligence for the Detection of Fetal Ultrasound Findings Concerning for Major Congenital Heart DefectsCarolyn M Zelop, Jennifer Lam-Rachlin, Alisa Arunamata, et al.
Obstetrics and Gynecology|October 16, 2025
Use of Artificial Intelligence-Based Software to Aid in the Identification of Ultrasound Findings Associated With Fetal Congenital Heart DefectsJennifer Lam-Rachlin, Rajesh Punn, Sarina K Behera, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|July 21, 2021
RobustSleepNet: Transfer Learning for Automated Sleep Staging at ScaleAntoine Guillot, Valentin Thorey
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|August 4, 2020
Dreem Open Datasets: Multi-Scored Sleep Datasets to Compare Human and Automated Sleep StagingAntoine Guillot, Fabien Sauvet, Emmanuel H During, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
AI vs Humans for the diagnosis of sleep apneaValentin Thorey, Albert Bou Hernandez, Pierrick J Arnal, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 18, 2020
Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the PolysomnogramAlexander Neergaard Olesen, Stanislas Chambon, Valentin Thorey, et al.
Frontiers in Human Neuroscience|March 24, 2018
Performance of an Ambulatory Dry-EEG Device for Auditory Closed-Loop Stimulation of Sleep Slow Oscillations in the Home EnvironmentEden Debellemaniere, Stanislas Chambon, Clemence Pinaud, et al.
Sleep|May 21, 2020
The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep stagingPierrick J Arnal, Valentin Thorey, Eden Debellemaniere, et al.
Obstetrics and Gynecology|August 7, 2025
Artificial Intelligence for the Detection of Fetal Ultrasound Findings Concerning for Major Congenital Heart DefectsCarolyn M Zelop, Jennifer Lam-Rachlin, Alisa Arunamata, et al.
Obstetrics and Gynecology|October 16, 2025
Use of Artificial Intelligence-Based Software to Aid in the Identification of Ultrasound Findings Associated With Fetal Congenital Heart DefectsJennifer Lam-Rachlin, Rajesh Punn, Sarina K Behera, et al.
Pageof 1