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2025 Journal Article Validation of manually scored multichannel frontal electroencephalography against polysomnography in a paediatric cohortSigurdardottir, Sigridur, Pitkänen, Henna, Korkalainen, Henri, Kainulainen, Samu, Serwatko, Marta, Olafsdottir, Kristin A., Sigurðardóttir, Sigurveig Þ., Clausen, Michael, Somaskandhan, Pranavan, Stražišar, Barbara G., Leppänen, Timo and Arnardottir, Erna Sif (2025). Validation of manually scored multichannel frontal electroencephalography against polysomnography in a paediatric cohort. Journal of Sleep Research, 34 (6) e70012. doi: 10.1111/jsr.70012 |
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2024 Conference Publication O004 Incorporating arousals into sleep vs. wakefulness classification outperforms traditional binary classification at 1-second epoch resolutionSomaskandhan, P., Korkalainen, H., Leppänen, T., Töyräs, J., Melehan, K., Wilson, D., Ruehland, W., Mann, D. and Terrill, P. (2024). O004 Incorporating arousals into sleep vs. wakefulness classification outperforms traditional binary classification at 1-second epoch resolution. Sleep DownUnder 2024, Gold Coast, QLD Australia, 16-19 October 2024. Oxford, United Kingdom: Oxford University Press. doi: 10.1093/sleepadvances/zpae070.004 |
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2024 Conference Publication Multi-channel frontal EEG – validation on manual sleep staging in a pediatric cohortSigurdardottir, S., Pitkänen, H., Korkalainen, H., Kainulainen, S., Serwatko, M., Olafsdottir, K.A., Sigurðardóttir, S.þ., Clausen, M., Somaskandhan, P., Stražišar, B.G., Leppänen, T. and Arnardóttir, E.S. (2024). Multi-channel frontal EEG – validation on manual sleep staging in a pediatric cohort. 17th World Sleep Congress, Rio de Janeiro, Brazil, 20-25 October 2023. Amsterdam, Netherlands: Elsevier. doi: 10.1016/j.sleep.2023.11.749 |
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2023 Journal Article Multicentre sleep‐stage scoring agreement in the Sleep Revolution projectNikkonen, Sami, Somaskandhan, Pranavan, Korkalainen, Henri, Kainulainen, Samu, Terrill, Philip I., Gretarsdottir, Heidur, Sigurdardottir, Sigridur, Olafsdottir, Kristin Anna, Islind, Anna Sigridur, Óskarsdóttir, María, Arnardóttir, Erna Sif and Leppänen, Timo (2023). Multicentre sleep‐stage scoring agreement in the Sleep Revolution project. Journal of Sleep Research, 33 (1) e13956, 1-13. doi: 10.1111/jsr.13956 |
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2023 Journal Article Deep learning-based algorithm accurately classifies sleep stages in preadolescent children with sleep-disordered breathing symptoms and age-matched controlsSomaskandhan, Pranavan, Leppänen, Timo, Terrill, Philip I., Sigurdardottir, Sigridur, Arnardottir, Erna Sif, Ólafsdóttir, Kristín A., Serwatko, Marta, Sigurðardóttir, Sigurveig Þ., Clausen, Michael, Töyräs, Juha and Korkalainen, Henri (2023). Deep learning-based algorithm accurately classifies sleep stages in preadolescent children with sleep-disordered breathing symptoms and age-matched controls. Frontiers in Neurology, 14 1162998, 1-12. doi: 10.3389/fneur.2023.1162998 |
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2022 Conference Publication A detailed analysis of multicentric sleep staging inter-rater variabilitiesSomaskandhan, P., Terrill, P., Korkalainen, H., Kainulainen, S., Leppänen, T., Islind, A., Grétarsdóttir, H. and Nikkonen, S. (2022). A detailed analysis of multicentric sleep staging inter-rater variabilities. 33rd annual scientific meeting of Australasian Sleep Association (ASA) & Australian and New Zealand Sleep Science Association (ANZSSA) Sleep DownUnder 2022, Brisbane, QLD Australia, 8-11 November 2022. Oxford, United Kingdom: Oxford University Press. doi: 10.1093/sleepadvances/zpac029.182 |
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2021 Conference Publication Deep learning enables accurate automatic sleep stage classification in a clinical paediatric populationSomaskandhan, P., Korkalainen, H., Terrill, P., Sigurðardóttir, S., Arnardóttir, E., Ólafsdóttir, K., Sigurðardóttir, S., Clausen, M., Töyräs, J. and Leppänen, T. (2021). Deep learning enables accurate automatic sleep stage classification in a clinical paediatric population. Sleep Down Under 2021: Australasian Sleep Association Conference, Online, 10-13 October 2021. Oxford, United Kingdom: Oxford University Press. doi: 10.1093/sleepadvances/zpab014.178 |
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2017 Conference Publication Identifying the optimal set of attributes that impose high impact on the end results of a cricket match using machine learningSomaskandhan, Pranavan, Wijesinghe, Gihan, Wijegunawardana, Leshan Bashitha, Bandaranayake, Asitha and Deegalla, Sampath (2017). Identifying the optimal set of attributes that impose high impact on the end results of a cricket match using machine learning. 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), Peradeniya, Sri Lanka, 15-16 December 2017. Danvers, MA USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/iciinfs.2017.8300399 |
