ArticleSleep medicine reviews2026
Artificial intelligence and sleep medicine II: A scoping review of applications, advancements, and future directions.
Article in Sleep medicine reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance of AI-Based Screening Tools for Obstructive Sleep Apnea Across Apnea-Hypopnea Index Thresholds: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Adult primary snoring: a modified Delphi consensus among Chinese otolaryngologists with AI-assisted evidence synthesis.Journal of thoracic disease · 2026Review
- CSPT-SleepNet: An Automatic Sleep Staging Framework Integrating Center-Driven Sequence Supervision and Multimodal Pyramid Token Encoding.Brain sciences · 2026Article
- Prediction of cognitive performance by demographics, sleep, and brain morphometry: machine learning findings from ENIGMA-Sleep Working Group.Research square · 2026Article
- Transformer-based deep learning approach for obstructive sleep apnea detection using single-lead ECG.Frontiers in artificial intelligence · 2026Article
- Beyond Algorithms: The Case for Standardized Reporting in AI Sleep Scoring.Nature and science of sleep · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundArtificial intelligence (AI) has rapidly advanced in sleep medicine, offering innovative solutions for sleep disorder management. The integration of AI technologies presents unprecedented opportunities to address longstanding challenges in diagnosis, monitoring, and treatment.
methodsThis scoping review summarizes current AI applications in sleep medicine following PRISMA-ScR. A comprehensive search was conducted across various databases from inception to 2024, following PRISMA-ScR guidelines. Eligible studies included original AI research, systematic reviews, and meta-analyses focusing on sleep medicine.
resultsAI models for obstructive sleep apnea (OSA) detection demonstrated accuracy between 85 % and 99 % in controlled settings, with outlier up to 99.9 %. Deep learning approaches for sleep staging and quality assessment match human expert performance. AI applications have extended to other disorders like insomnia and narcolepsy. Wearable technologies and non-contact sensors enable continuous monitoring outside laboratory settings, with some achieving sensitivity >96 % and specificity >97 % for OSA detection. Significant real-world validation gaps persist.
conclusionsWhile AI shows transformative potential in sleep medicine, implementation challenges remain. Future research should prioritize multicenter validation, ethical governance, and culturally inclusive AI frameworks to ensure safe and equitable clinical translation. Addressing ethical considerations and standardizing methodological reporting are essential for widespread adoption of these technologies in clinical practice.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.