Sleep Disorders

Sleep loss overrides sleep-preparatory behavior to promote sleep.

In the period preceding sleep, humans and other animals display a stereotyped repertoire of behaviors-including hygiene-related activities and preparing a place to sleep. Evidence suggests that this pre-sleep phase actively contributes to sleep initiation and quality. Nonetheless, individuals can sometimes fall asleep without preparation, even under undesirable circumstances. These abrupt transiti...

Exploration and validation of potential diagnostic biomarkers of PANoptosis in periodontitis using bioinformatics approaches.

BACKGROUND: Periodontitis represents a chronic inflammatory disease resulting from the interaction between plaque-associated microorganisms and the host immune response. PANoptosis, a newly recognized programmed cell death, is linked to multiple inflammatory disorders. However, its role in periodontitis pathogenesis and diagnostic potential remains unclear. This study aimed to identify key PANopto...

On the usage of artificial intelligence for identifying main attributes and predicting neonatal sepsis.

During the neonatal period, newborns are more susceptible to developing conditions and diseases due to their fragility of the transition and adaptatio...

Wireless, skin-interfaced multimodal sensing system for continuous psychophysiological monitoring-A wearable polygraph device.

Accurate, continuous monitoring of psychophysiological states is central to understanding stress and autonomic dysfunction across diverse medical cont...

Noninvasive neurophysiological diagnostics of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a scoping review.

BACKGROUND: Delayed cerebral ischemia (DCI) is a major complication following aneurysmal subarachnoid hemorrhage (aSAH), affecting outcomes. Given its...

Machine Learning-Based Multidimensional Oximetry for Obstructive Sleep Apnea Screening: Development and External Validation.

BACKGROUND: Obstructive sleep apnea (OSA) affects nearly one billion people globally and poses a substantial public health threat. Effective and acces...

Development and validation of a clinlabomics-based machine-learning model for noninvasive risk stratification of moderate-to-severe OSA.

PURPOSE: Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder strongly associated with adverse cardiometabolic and neurocognitive outcom...

Global Perspectives on CNS Drug Innovation: Achievements, Barriers, and Priorities for the Next Decade.

BACKGROUND: Over the past decade, neuropsychopharmacology has shifted from stagnation to momentum, with first-in-class mechanisms and biomarker-enable...

Machine learning-based prediction of ventilator therapeutic pressure for optimized CPAP titration.

BACKGROUND: Accurate prediction of therapeutic pressure for Continuous Positive Airway Pressure (CPAP) therapy is essential for effective treatment of...

[Dynamic assessment of upper airway in obstructive sleep apnea patients with a focus on drug-induced sleep endoscopy].

The key pathophysiological feature of obstructive sleep apnea（OSA） is dynamic collapse of the upper airway during sleep. Polysomnography（PSG） and awak...

Machine learning to diagnose, classify and predict phenoconversion in isolated REM sleep behavior disorder.

Rapid eye movement (REM) sleep behaviour disorder (RBD), particularly its idiopathic/isolated form (iRBD), is a prodromal marker for α-synucleinopathi...

Deep learning-based automatic scoring of drug-induced sleep endoscopy in obstructive sleep apnea.

Polysomnography is the standard tool for assessing obstructive sleep apnea (OSA) severity; however, it does not provide information regarding the anat...

Boon or a bane: Different usage of LLM correlates with mental health.

BACKGROUND: While large language models (LLMs) are increasingly integrated into daily life, the relationship between purpose-specific usage and mental...

Monitoring airline pilot mental health: a 3PM framework utilising digital phenotyping and AI.

The aeromedical certification of commercial airline pilots relies on periodic, self-disclosure-dependent assessments. However, this reactive model lac...

Artificial intelligence in sleep medicine I: Diagnosis, treatment, care, and research.

Artificial intelligence (AI) is transforming sleep medicine (SM) through improved diagnostics, therapeutics, and research. AI enhances diagnostic accu...

Simplified and accurate approach to sleep disorder prediction using body composition metrics: a development and validation study.

Predicting the risk of sleep disorders such as insomnia, obstructive sleep apnea (OSA), and comorbid insomnia and sleep apnea (COMISA) typically requi...

The Insomnia EEG Score: a new tool for the classification of people with poor sleep.

Quantitative features could help objectively identify and grade insomnia severity, though there is currently no pathophysiological biomarker of insomn...

Multimodal cardiovascular risk profiling using self-supervised learning of polysomnography.

STUDY OBJECTIVES: Polysomnography (PSG) provides a comprehensive assessment of brain, cardiac, and respiratory activity during sleep. While it is wide...

Automatic sleep staging from CPAP airflow using a dual fusion multi-period convolutional neural network.

BACKGROUND: Continuous Positive Airway Pressure (CPAP) therapy is the standard treatment for obstructive sleep apnea-hypopnea syndrome, yet its use as...

Digital Technology for Sleep Symptoms in Parkinson's Disease: A Scoping Review.

Sleep disturbances are highly prevalent and clinically significant non-motor features of Parkinson's disease (PD). Although in-laboratory polysomnogra...