Article

Automated Sleep Stage and Event Detection Algorithms Using Quality-Controlled PSG Annotations

2025-12-17

Abstract excerpt

<h4>Study Objectives</h4> To develop machine-learning models for sleep stage classification, arousal detection, and respiratory event detection from overnight polysomnography, and to evaluate their performance relative to expert scorers. <h4>Methods</h4> Overnight polysomnography recordings were obtained from healthy participants and participants referred for suspected sleep-disordered breathing. Four certified...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 5d334c8b-70d2-5e52-b88b-de9b86cad8e9
DOI: 10.64898/2025.12.15.25342334

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Automated Sleep Stage and Event Detection Algorithms Using Quality-Controlled PSG AnnotationsDOI 10.64898/2025.12.15.25342334Read

Multimodal sleep stage classification and label-free abnormality scoring in mid-to-older adultsSemantic proximity Read

Expert-level probabilistic breathing event detector informs phenotyping of sleep apnea.Semantic proximity Read

SleepGPT: A Sleep Stage Language Model for Efficient Sleep AssessmentSemantic proximity Read

Temporally Continuous Automated Sleep-Wake Classification Using Deep LearningSemantic proximity Read

A Zero-Burden Sleep Foundation Model Built on Cardiorespiratory Signals from 1,400,000+ Hours of Multi-Ethnic Sleep RecordingsSemantic proximity Read

Advances in Sleep Stage Detection Using Wearable Physiological Signals: A Systematic ReviewSemantic proximity Read

A Multimodal Sleep Foundation Model for Disease PredictionSemantic proximity Read

Status and Opportunities of Machine Learning Applications in Obstructive Sleep Apnea: A Narrative ReviewSemantic proximity Read

A Unified Flexible Large Polysomnography Model for Sleep Staging and Mental Disorder DiagnosisSemantic proximity Read

Optimized Machine Learning Algorithms for the Classification and Diagnosis of Sleep DisordersSemantic proximity Read

A Unified Flexible Large Polysomnography Model for Sleep Staging and Brain Disorder DiagnosisSemantic proximity Read

State-of-the-art Sleep Arousal Detection Evaluated on a Comprehensive Clinical DatasetSemantic proximity Read