Artificial Intelligence in Sleep Medicine

Dear Colleagues,

Background & history of this topic:

Artificial intelligence (AI) entered sleep medicine just a few years ago mainly as a research tool. It has since evolved to aid in clinical evaluation and become an important addition to the tools available for detecting and assessing sleep disorders. Today, AI is an integral part of sleep medicine and will likely play an even bigger role in the future as wearable and home-based sleep trackers become more prevalent.

Aim and scope of the Special Issue:

This Special Issue aims to present cutting-edge research on AI applications in sleep medicine, covering normal sleep patterns and the full spectrum of sleep disorders. We welcome original research as well as review articles on topics including narcolepsy/hypersomnias, parasomnias, restless legs syndrome, sleep apnea, and circadian rhythm disorders. Studies exploring the links between sleep and health are of interest, particularly cardiovascular diseases and brain health/neurodegeneration. We also invite opinion pieces on how AI is changing the sleep medicine field.

Cutting-edge research:

• AI-assisted diagnosis of sleep disorders based on clinical questionnaires, wearable data, nearables, imaging, and other digital biomarkers;
• Neural network models for optimizing treatment of sleep apnea, insomnia, and other sleep disorders;
• Natural language processing for analyzing patient sleep logs and clinical notes;
• Predictive analytics to identify individuals at risk for sleep disturbances using demographics, medical history, and lifestyle data;
• Algorithms for automated scoring and classification of sleep stages and events using polysomnography, actigraphy, and other physiological data;
• Novel sensors and wearable devices enhanced by machine learning for sleep monitoring and phenotype discovery;
• AI for discovering connections between sleep and other health conditions such as Alzheimer's, depression, obesity, etc.;
• Improving adherence and efficacy of digital CBT for insomnia using reinforcement learning and virtual agents;
• Ethical implications of using AI in sleep medicine clinical practice and research.

What kinds of papers we are soliciting:

• Original research articles demonstrating novel applications of AI in sleep medicine;
• Review articles synthesizing major themes, techniques, challenges, and opportunities in the field;
• Perspective pieces on the impacts of AI on the sleep medicine clinician workflow, training, etc.;
• Commentaries discussing limitations, best practices, and future outlook for AI in sleep research and care;
• Viewpoint articles highlighting implications for health policy, regulation, and access to care;
• Technical reports detailing new AI methodologies tailored to sleep data and disorders;
• Pilot studies examining feasibility of implementing AI tools in clinical settings;
• Meta-analyses and systematic reviews of AI accuracy for sleep assessment across multiple studies.

Dr. Ambra Stefani
Dr. Wolfgang Ganglberger
Guest Editors

Manuscript Submission Information

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• sleep
• artificial intelligence
• machine-learning
• brain health
• sleep scoring
• sleep disorders
• digital health
• wearables
• digital biomarkers