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Riku Huttunen

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

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Biomolecules|March 6, 2021
Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization PatternsKaisa Liimatainen, Riku Huttunen, Leena Latonen, et al.
IEEE Transactions on Bio-Medical Engineering|October 20, 2025
Direct Quantification of Uncertainty in Deep Learning-Based Automatic Sleep StagingMiika Vainikka, Riku Huttunen, Samu Kainulainen, et al.
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
Optimal Electroencephalogram and Electrooculogram Signal Combination for Deep Learning-based Sleep StagingMasoumeh Tashakori, Matias Rusanen, Tuomas Karhu, et al.
Sleep|June 5, 2021
Assessment of obstructive sleep apnea-related sleep fragmentation utilizing deep learning-based sleep staging from photoplethysmographyRiku Huttunen, Timo Leppänen, Brett Duce, et al.
IEEE Transactions on Bio-Medical Engineering|November 28, 2022
A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event DetectionRiku Huttunen, Timo Leppanen, Brett Duce, et al.
ERJ Open Research|December 2, 2020
Increased nocturnal arterial pulsation frequencies of obstructive sleep apnoea patients is associated with an increased number of lapses in a psychomotor vigilance taskSamu Kainulainen, Brett Duce, Henri Korkalainen, et al.
IEEE Journal of Biomedical and Health Informatics|April 6, 2023
Generalizable Deep Learning-Based Sleep Staging Approach for Ambulatory Textile Electrode Headband RecordingsMatias Rusanen, Riku Huttunen, Henri Korkalainen, et al.
Journal of Sleep Research|October 23, 2024
Retrospective validation of automatic sleep analysis with grey areas model for human-in-the-loop scoring approachMatias Rusanen, Gabriel Jouan, Riku Huttunen, et al.
Pageof 1

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

Sort By:
Pageof 1
Biomolecules|March 6, 2021
Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization PatternsKaisa Liimatainen, Riku Huttunen, Leena Latonen, et al.
IEEE Transactions on Bio-Medical Engineering|October 20, 2025
Direct Quantification of Uncertainty in Deep Learning-Based Automatic Sleep StagingMiika Vainikka, Riku Huttunen, Samu Kainulainen, et al.
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
Optimal Electroencephalogram and Electrooculogram Signal Combination for Deep Learning-based Sleep StagingMasoumeh Tashakori, Matias Rusanen, Tuomas Karhu, et al.
Sleep|June 5, 2021
Assessment of obstructive sleep apnea-related sleep fragmentation utilizing deep learning-based sleep staging from photoplethysmographyRiku Huttunen, Timo Leppänen, Brett Duce, et al.
IEEE Transactions on Bio-Medical Engineering|November 28, 2022
A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event DetectionRiku Huttunen, Timo Leppanen, Brett Duce, et al.
ERJ Open Research|December 2, 2020
Increased nocturnal arterial pulsation frequencies of obstructive sleep apnoea patients is associated with an increased number of lapses in a psychomotor vigilance taskSamu Kainulainen, Brett Duce, Henri Korkalainen, et al.
IEEE Journal of Biomedical and Health Informatics|April 6, 2023
Generalizable Deep Learning-Based Sleep Staging Approach for Ambulatory Textile Electrode Headband RecordingsMatias Rusanen, Riku Huttunen, Henri Korkalainen, et al.
Journal of Sleep Research|October 23, 2024
Retrospective validation of automatic sleep analysis with grey areas model for human-in-the-loop scoring approachMatias Rusanen, Gabriel Jouan, Riku Huttunen, et al.
Pageof 1