ArticleFrontiers in genetics2022
Multiple Machine Learning Methods Reveal Key Biomarkers of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Treatment.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed, 9 citations in OpenAlex.
- Integration of Transcriptomics With Interpretable Artificial Intelligence for Identifying Molecular Signatures of Physiological Stress in Sleep Deprivation.Journal of cellular and molecular medicine · 2026Article
- Automated analysis of the American Academy of Sleep Medicine Inter-Scorer Reliability gold-standard polysomnogram dataset.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- The Link Between Sleep-Related Breathing Disorders and Idiopathic Pulmonary Fibrosis: Pathophysiological Mechanisms and Treatment Options-A Review.Journal of clinical medicine · 2025Review
- Preliminary evidence of immune infiltration and neutrophil degranulation in peripheral blood of non-obese OSA patients related to cognitive decline.Scientific reports · 2025Article
- Advances in Machine Learning Prediction Models for the Screening of Obstructive Sleep Apnea in Adults.Nature and science of sleep · 2025Review
- [Sleep Innovation].Open respiratory archives · 2024Review
- The role of artificial intelligence in the treatment of obstructive sleep apnea.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale · 2023Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obstructive sleep apnea (OSA) is a worldwide health issue that affects more than 400 million people. Given the limitations inherent in the current conventional diagnosis of OSA based on symptoms report, novel diagnostic approaches are required to complement existing techniques. Recent advances in gene sequencing technology have made it possible to identify a greater number of genes linked to OSA. We identified key genes in OSA and CPAP treatment by screening differentially expressed genes (DEGs) using the Gene Expression Omnibus (GEO) database and employing machine learning algorithms. None of these genes had previously been implicated in OSA. Moreover, a new diagnostic model of OSA was developed, and its diagnostic accuracy was verified in independent datasets. By performing Single Sample Gene Set Enrichment Analysis (ssGSEA) and Counting Relative Subsets of RNA Transcripts (CIBERSORT), we identified possible immunologic mechanisms, which led us to conclude that patients with high OSA risk tend to have elevated inflammation levels that can be brought down by CPAP treatment.
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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.