ArticleDiagnostics (Basel, Switzerland)2021
Prediction Models for Obstructive Sleep Apnea in Korean Adults Using Machine Learning Techniques.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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.
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Who cites it
19 citing papers in PubMed, 42 citations in OpenAlex.
- Development of a machine learning model using systemic and ophthalmic parameters to detect sleep-disordered breathing in glaucoma patients.Japanese journal of ophthalmology · 2026Article
- Development and Explainable Machine Learning Validation of a Novel Sleep Disturbance Ratio for Obstructive Sleep Apnea Severity Assessment.Diagnostics (Basel, Switzerland) · 2026Article
- Machine Learning-Based Multidimensional Oximetry for Obstructive Sleep Apnea Screening: Development and External Validation.JMIR medical informatics · 2026Article
- Identification of Comorbidities in Obstructive Sleep Apnea Using Diverse Data and a One-Dimensional Convolutional Neural Network.Sensors (Basel, Switzerland) · 2026Observational
- Integrating Complete Blood Count Parameters with Demographic Characteristics for Obstructive Sleep Apnea Prediction in Chinese Adults: A Machine Learning Approach.Nature and science of sleep · 2026Article
- A novel machine learning model for screening the risk of obstructive sleep apnea using craniofacial photography with questionnaires.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- Ferroptosis as a Potential Mechanism in the Pathophysiology of Obstructive Sleep Apnea Syndrome.Nature and science of sleep · 2025Review
- Advances in Machine Learning Prediction Models for the Screening of Obstructive Sleep Apnea in Adults.Nature and science of sleep · 2025Review
- An Artificial Intelligence-Based Non-Invasive Approach for Cardiovascular Disease Risk Stratification in Obstructive Sleep Apnea Patients: A Narrative Review.Reviews in cardiovascular medicine · 2024Review
- Enhanced machine learning approaches for OSA patient screening: model development and validation study.Scientific reports · 2024Article
- OSApredictor: A tool for prediction of moderate to severe obstructive sleep apnea-hypopnea using readily available patient characteristics.Computers in biology and medicine · 2024Article
- UltraAIGenomics: Artificial Intelligence-Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and Genomics Features for Preventive, Personalized and Precision Medicine: A Narrative Review.Reviews in cardiovascular medicine · 2024Review
- Development and application of a machine learning-based predictive model for obstructive sleep apnea screening.Frontiers in big data · 2024Article
- Application of various machine learning techniques to predict obstructive sleep apnea syndrome severity.Scientific reports · 2023Article
- Predicting the Severity of Lockdown-Induced Psychiatric Symptoms with Machine Learning.Diagnostics (Basel, Switzerland) · 2022Article
- Classification of severe obstructive sleep apnea with cognitive impairment using degree centrality: A machine learning analysis.Frontiers in neurology · 2022Article
- Towards Validating the Effectiveness of Obstructive Sleep Apnea Classification from Electronic Health Records Using Machine Learning.Healthcare (Basel, Switzerland) · 2021Article
- A multimodal multi-agent LLM framework for identifying key drivers of sleep disorders.Frontiers in neurologyArticle
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Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
This study aimed to investigate the applicability of machine learning to predict obstructive sleep apnea (OSA) among individuals with suspected OSA in South Korea. A total of 92 clinical variables for OSA were collected from 279 South Koreans (OSA,
Indexed as
Identifiers
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.