Rebecca Sophia Sylvester
About
PhD student in the Trondheim Sleep and Chronobiology Research Group (SACR) at NTNU, Department of Mental Health. I am interested in the application of (explainable) artificial intelligence in medicine, specifically mental disorders. As part of the AI-MENT project, I am working on sleep/wake prediction and automatic human behavioral pattern recognition, specifically the early prediction of aggressive behavior, in psychiatric patients from radar data. To this end, I employ different machine and deep learning techniques, among them supervised classification, anomaly detection, and self-supervised learning.
Publications
2024
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Sylvester, Rebecca Sophia;
Sagehorn, Merle;
Gruber, Thomas;
Atzmueller, Martin;
Schöne, Benjamin Joachim.
(2024)
SHAP value-based ERP analysis (SHERPA): Increasing the sensitivity of EEG signals with explainable AI methods.
Behavior Research Methods
Academic article
Journal publications
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Sylvester, Rebecca Sophia;
Sagehorn, Merle;
Gruber, Thomas;
Atzmueller, Martin;
Schöne, Benjamin Joachim.
(2024)
SHAP value-based ERP analysis (SHERPA): Increasing the sensitivity of EEG signals with explainable AI methods.
Behavior Research Methods
Academic article
Teaching
Courses
Outreach
2023
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PosterSylvester, Sophia; Heglum, Hanne Siri Amdahl. (2023) Translating radar data into sleep insights: A comparative study of machine learning models. World Sleep Society World Sleep Congress , Rio de Janeiro 2023-10-20 - 2023-10-25
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LectureSylvester, Sophia. (2023) Comparing machine learning models to assess sleep from radar data in healthy individuals. SOVno Nasjonal søvnkonferanse , Solstrand 2023-09-14 - 2023-09-15
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PosterSylvester, Sophia. (2023) Radar-based sleep monitoring in healthy individuals: A comprehensive comparative analysis of machine learning models. NTNU Helse A healthy future , Trondheim 2023-10-05 - 2023-10-05