Sleep disorders burden healthcare systems due to laborious diagnostics and limited workforce capacities. However, a wealth of data collected from sleep recordings, patient histories, and electronic medical records remains underutilized in current practices. Additionally, emerging data from wearables, nearables, and apps hold immense potential for understanding the long-term implications of sleep disorders.
Artificial intelligence (AI) may revolutionize sleep research and medicine by enhancing diagnostic efficiency and accuracy, predicting outcomes, and characterizing patient and disorder traits for optimized and personalized care. However, it is crucial to ensure the ethical design, development, and implementation of these methods while considering data privacy, transparency, validation best practices, and method reliability and generalizability.
This call for papers explores the latest advancements in AI in sleep medicine and research. It seeks to emphasize the translation of methodologies into clinical practice, focusing on the technical aspects while acknowledging the importance of ethics.
Topics of interest include:
- Automatic sleep study scoring
- Novel methods for sleep disorder detection
- Utilization of subjective and objective data
- Integration in electronic medical record systems
- Minimally invasive data collection for screening and long-term follow-up of the general population
- Validation and implementation
- Discussions on best practices, ethical considerations, and practical implementation of AI in sleep research and medicine
We welcome submissions of original research, reviews, perspectives, and commentaries. Join us in contributing to the conversation on the role of AI in sleep medicine and the considerations surrounding the translation to clinical practice. This collection will serve as a valuable resource for researchers, practitioners, and policymakers interested in the intersection of AI and sleep research.
Submission Instructions:
All manuscripts submitted to this Article Collection will undergo full peer-review; Guest Advisors will not be handling submitted articles. Please review the journal’s aims and scope and author submission instructions prior to submission.
Please submit your manuscript through the Dovepress website. During submission, enter the promo code AUCFK to indicate that your article should be considered for this Collection.
The manuscript submission deadline is 31 December 2023.
If you have any questions about this Article Collection, please contact Krista Thom at [email protected].
Guest Advisors:
Jon Skirnir Agustsson is an accomplished research leader and the VP of Artificial Intelligence and Data Science at Nox Medical. After earning a Ph.D. in experimental physics from Basel University, he joined Nox Medical as a research manager in 2015. He leads a diverse team dedicated to transforming sleep medicine through the application of artificial intelligence (AI) and machine learning in sleep diagnostics. Their work encompasses the development of cutting-edge AI analysis, clinical validation, and research. Furthermore, they collaborate closely with regulatory bodies and industry stakeholders, to ensure that the AI medical devices are safe and effective for use in clinical practice. The team's AI analysis solutions are used globally in medical devices and in research.
Anna Sigridur Islind has a Ph.D. in Informatics, focusing on medical informatics and data-driven healthcare from University West in Sweden. She is an Associate Professor at the Department of Computer Science at Reykjavik University and is the director of the research centre CISDAS, Centre for Information Systems and Data Science Research. Moreover, she is the leader of the digital innovation in the Sleep Revolution project, a large-scale Horizon 2020 project with 39 partners across Europe funded by the European Union and is the program manager for the M.Sc. in Digital Health, a novel multi-disciplinary study line at Reykjavik University. She has published 75 peer reviewed papers most of which focus on doing good through being socially aware and ethically driven when designing, developed and using digital ecosystems, artificial intelligence, and data, specifically within healthcare.
Henri Korkalainen received his Ph.D. degree in medical physics from the University of Eastern Finland in 2020 and the Title of Docent/Adjunct Professor in 2022. He joined the Sleep Technology and Analytics Research Group in 2018 and he is currently working with the Department of Technical Physics, University of Eastern Finland, and the Diagnostic Imaging Center, Kuopio University Hospital. His research interests include the development of deep learning methods in medical diagnostics, mainly in the field of sleep medicine, and the simplification of current diagnostic recordings with the development of artificial intelligence applied to easily applicable and wearable sensors.
Disclosure Statement: Jon Skirnir Agustsson is an employee of Nox Medical ehf, Reykjavík, Iceland. AI and HK declare no conflict of interest.
