Sleep Disorders

Explainable Machine-Learning Model for Predicting Severe Obstructive Sleep Apnea in Patients Undergoing Metabolic Bariatric Surgery.

BACKGROUND: Severe obstructive sleep apnea (SOSA) is associated with an increased risk of perioperat...

"Temporarily Forgetting Stress": Exploring the Multimodal Features and Audience Experience of AI-Generated Psychological Healing Videos.

This study examines the content characteristics, audience interaction, and experience feedback of ar...

Artificial Intelligence Diagnosis of Obstructive Sleep Apnea Using Overnight Pulse Oximetry: A Systematic Review and Bayesian Meta-Analysis.

BACKGROUND: Obstructive sleep apnea (OSA) affects 38% of the population, yet over 90% of cases remai...

Machine learning-based insomnia symptom risk classification model for residents of Hebei province.

OBJECTIVES: The aim is to develop and externally validate a machine learning-based risk classificati...

PANDA pediatric arousal neural detection architecture.

We developed and validated PANDA, a deep-learning model for pediatric arousal detection in polysomno...

Neuroimaging-derived biotypes of self-reported insomnia symptoms are differentially associated with affective symptoms.

BACKGROUND: Sleep problems are among the most prevalent health complaints during adolescence and sho...

Development and validation of machine learning models for obstructive sleep apnea risk stratification in high-risk pregnant women.

BACKGROUND: Obstructive sleep apnea (OSA) affects approximately 15% of pregnancies and is associated...

Clock gene signature predicts insomnia and links to sleep/circadian parameters.

Chronic Insomnia is a prevalent sleep disorder that remains difficult to diagnose due to subjective ...

Artificial intelligence-based automated sleep staging using heart rate variability: Assessment of performance and clinical prospects.

Background Some artificial intelligence models use heart rate variability (HRV) features to classify...

Energy-efficient real-time 4-stage sleep classification at 10-second resolution.

Sleep stage classification is critical for diagnosing and managing disorders like sleep apnea and in...

A machine learning-based screening tool for classifying post-traumatic stress disorder in firefighters: Firefighter Latent Risk Evaluation (FLARE).

BACKGROUND: The prevalence of post-traumatic stress disorder (PTSD) among South Korean firefighters ...

Innovative screening for OSAS in patients with head and neck cancer using the apneal application: Protocol for a prospective single-centre study.

INTRODUCTION: OSAS is a common yet underdiagnosed condition, particularly among patients with head a...

Development of Data-Driven Models for Just-in-Time Digital Self-Management Advice to Improve Physical Functioning in Hip and Knee Osteoarthritis: Protocol for the e-cOAch Cross-Over Study.

BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee ost...

Machine learning for scalable obstructive sleep apnea risk screening using digital phenotyping from wearable devices and clinical scales.

Obstructive sleep apnea (OSA) is common yet frequently underdiagnosed, partly because overnight poly...

Neuroprotective effects of Chaihu-Longgu-Muli Decoction in an insomnia-depression comorbidity model via Galectin-3-dependent JAK2/STAT3 inhibition.

ETHNOPHARMACOLOGICAL RELEVANCE: Chaihu-Longgu-Muli Decoction (CLMD) is a classical Traditional Chine...

Artificial intelligence for nocturnal oximetry-based diagnosis of OSAS in children younger than 2 years: time to end the polysomnography monocracy?

Hypnodensity sleep metrics from fingertip photoplethysmography are better associated with daytime sleepiness and fatigue than traditional metrics from polysomnography.

BACKGROUND: Traditional sleep metrics from polysomnography are often limited by the hypnogram, in wh...

Peripheral and central immune features in insomnia: Integrative bulk and single-cell transcriptomic analyses reveal core hub genes and candidate compounds.

Insomnia is closely associated with immune dysregulation, yet the overall pattern of peripheral-cent...

Artificial intelligence in sleep diagnostics for children under 2 years of age: state of the evidence and future directions.

BACKGROUND: Artificial intelligence (AI) has advanced rapidly in adult sleep medicine, but its role ...

Quantitative sleep EEG identifies CSF core biomarker-related subgroups in Alzheimer's disease.

Early detection and biological characterization of Alzheimer's disease (AD) remain challenging, as c...

Non-contact on-device detection of obstructive sleep apnea from infrared video.

Obstructive sleep apnea (OSA) affects nearly one billion people worldwide, yet most cases remain und...