Göktepe-Kavis, Pinar; Aellen, Florence M.; Alnes, Sigurd L.; Tzovara, Athina (2024). Sleep research in the era of AI. Clinical and translational neuroscience, 8(1) MDPI 10.3390/ctn8010013
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The field of sleep research is both broad and rapidly evolving. It spans from the diagnosis of sleep-related disorders to investigations of how sleep supports memory consolidation. The study of sleep includes a variety of approaches, starting with the sole focus on the visual interpretation of polysomnography characteristics and extending to the emergent use of advanced signal processing tools. Insights gained using artificial intelligence (AI) are rapidly reshaping the understanding of sleep-related disorders, enabling new approaches to basic neuroscientific studies. In this opinion article, we explore the emergent role of AI in sleep research, along two different axes: one clinical and one fundamental. In clinical research, we emphasize the use of AI for automated sleep scoring, diagnosing sleep-wake disorders and assessing measurements from wearable devices. In fundamental research, we highlight the use of AI to better understand the functional role of sleep in consolidating memories. While AI is likely to facilitate new advances in the field of sleep research, we also address challenges, such as bridging the gap between AI innovation and the clinic and mitigating inherent biases in AI models. AI has already contributed to major advances in the field of sleep research, and mindful deployment has the potential to enable further progress in the understanding of the neuropsychological benefits and functions of sleep.
Item Type: |
Journal Article (Further Contribution) |
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Division/Institute: |
08 Faculty of Science > Institute of Computer Science (INF) 04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology 08 Faculty of Science > Institute of Computer Science (INF) > Cognitive Computational Neuroscience (CCN) |
UniBE Contributor: |
Göktepe, Pinar, Aellen, Florence Marcelle, Alnes, Sigurd Lerkerød, Tzovara, Athina |
Subjects: |
000 Computer science, knowledge & systems 600 Technology > 610 Medicine & health 500 Science > 510 Mathematics |
ISSN: |
2514-183X |
Publisher: |
MDPI |
Language: |
English |
Submitter: |
Athina Tzovara |
Date Deposited: |
14 Mar 2024 08:52 |
Last Modified: |
14 Mar 2024 09:01 |
Publisher DOI: |
10.3390/ctn8010013 |
BORIS DOI: |
10.48350/194222 |
URI: |
https://boris.unibe.ch/id/eprint/194222 |
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