Sleep Disorders

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 which each 30-s epoch is classified into one of the five sleep stages. This oversimplifies sleep stage continuity and fragmented sleep, typical in sleep-disordered breathing (SDB). Deep learning offers more dynamic sleep modelling with a higher temporal resolution by providing probabilities for each s...

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-central immune disequilibrium and its underlying molec...

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 in children under 2 years old remains unclear. Thi...

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 current diagnostic approaches rely on invasive cere...

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 undiagnosed because standard testing requires overnig...

Substance-induced manic psychosis in which delusions were corroborated by a chatbot - case report.

BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...

Week-ahead prediction of depressive episodes using wearable-derived circadian biomarkers: A multicenter deep learning study with risk-based operating thresholds.

Early detection of depressive episodes is important because shorter duration of untreated illness is associated with better outcomes, yet routine care...

Integration of Transcriptomics With Interpretable Artificial Intelligence for Identifying Molecular Signatures of Physiological Stress in Sleep Deprivation.

Sleep deprivation induces systemic physiological stress accompanied by transcriptomic remodelling and immune dysregulation, yet objective molecular in...

Artificial intelligence in emergency mechanical ventilation: a prospective observational comparison with emergency physician ventilator settings.

BACKGROUND: Artificial intelligence (AI) has the potential to support clinicians in high-risk and complex decision-making processes, such as mechanica...

Machine learning-assisted meta-analysis reveals melatonin crosstalk regulating plant growth plasticity under heavy metal stress.

Heavy metal (HM) pollution is a traditional and ongoing global ecological issue that requires continuous attention. Although studies have focused on h...

Predicting sleep state from continuous positive airway pressure flow in patients with obstructive sleep apnea.

INTRODUCTION: The first line treatment for obstructive sleep apnea (OSA) is continuous positive airway pressure (CPAP). CPAP adherence is assessed by ...

Features and functionality of the Iterapi platform for internet-based psychological treatments: An update.

Internet-based cognitive behaviour therapy (ICBT) is now a well-established treatment modality supported by numerous controlled trials. Platforms for ...

A Two-Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort.

OBJECTIVE: Isolated rapid-eye-movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due ...

Integrated computational and experimental analysis explores FOLH1 expression patterns across cancers and nominates melatonin as a potential modulator in prostate cancer models.

BACKGROUND: Growing evidence indicates that Folate Hydrolase 1 (FOLH1, also known as prostate-specific membrane antigen, PSMA) is aberrantly expressed...

[Automated analysis of mandibular movements for the screening of obstructive sleep apnea].

INTRODUCTION: Obstructive sleep apnea syndrome (OSAS) is a highly prevalent condition, particularly among at-risk populations such as patients with ob...

The Brain Imaging and Neurophysiology Dataset of large-scale multimodal neural data.

The Brain Imaging and Neurophysiology Dataset (BIND) represents one of the largest multi-institutional, multimodal, clinical neuroimaging repositories...

A Multi-Feature Fusion Framework for Automated Classification of Obstructive and Central Hypopneas in Polysomnography.

OBJECTIVE: This study aims to develop and validate a fully automated, interpretable machine learning system for the precise classification of obstruct...

A Multimodal Learning Framework for Detecting Systemic Hypertension in Sleep Apnea Patients Using ECG and PPG Signals.

Systemic hypertension (HTN) is a major cardiovascular comorbidity in patients with obstructive sleep apnea (OSA), yet these conditions are often diagn...

Connected parents, connected children: the relationship of smartphone, social media, and AI with parenting and children's tech consumption in Türkiye.

BACKGROUND: The objective of this study is to investigate parental utilization of smartphones, engagement with social media, and adoption of artificia...