AIMC Topic: Sleep Wake Disorders

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Relationship between obstructive sleep apnea cardiac complications and sleepiness in children with Down syndrome.

Sleep medicine
OBJECTIVE/BACKGROUND: Children with Down syndrome (DS) have a high rate of pulmonary hypertension and sleepiness. They also have a high prevalence of obstructive sleep apnea syndrome (OSAS). We hypothesized that OSAS was associated with cardiovascula...

Towards an Integrative Account of Potential Mechanisms Mediating the Path From Sleep Dysfunction to Hallucinations.

Schizophrenia bulletin
BACKGROUND: Sleep dysfunction shares a bidirectional relationship with hallucinatory experiences, with the strongest path from sleep dysfunction to the occurrence of hallucinatory experiences. This review aimed to identify potential mechanisms throug...

Hugan Tiaoshen Formula Improves the Comorbid Mechanism of Schizophrenia and Sleep Disorder via Multitarget Interaction Network.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
This study aims to integrate cross-disease omics data and perform multidimensional analysis to uncover the molecular basis of schizophrenia (SCZ) and sleep disorder (SD) comorbidity and to systematically analyze the potential mechanism of the Hugan T...

Big data approaches for novel mechanistic insights on sleep and circadian rhythms: a workshop summary.

Sleep
The National Center on Sleep Disorders Research of the National Heart, Lung, and Blood Institute at the National Institutes of Health hosted a 2-day virtual workshop titled Big Data Approaches for Novel Mechanistic Insights on Disorders of Sleep and ...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Scientific reports
Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disorders early is essential for effective treatment, which traditionally relies on polysomnogram (PSG) t...

Identifying Symptom Information in Clinical Notes Using Natural Language Processing.

Nursing research
BACKGROUND: Symptoms are a core concept of nursing interest. Large-scale secondary data reuse of notes in electronic health records (EHRs) has the potential to increase the quantity and quality of symptom research. However, the symptom language used ...

Wearable Artificial Intelligence for Sleep Disorders: Scoping Review.

Journal of medical Internet research
BACKGROUND: Worldwide, 30%-45% of adults have sleep disorders, which are linked to major health issues such as diabetes and cardiovascular disease. Long-term monitoring with traditional in-lab testing is impractical due to high costs. Wearable artifi...

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to investigate a predictive model for sleep efficiency and its associated features in older adults living...

Classification of Sleep-Wake State in Ballistocardiogram system based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sleep state classification is essential for managing and comprehending sleep patterns, and it is usually the first step in identifying sleep disorders. Polysomnography (PSG), the gold standard, is intrusive and inconvenient for regular/long-term slee...

Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nowadays, high amounts of data can be acquired in various applications, spurring the need for interpretable data representations that provide actionable insights. Algorithms that yield such representations ideally require as little a priori knowledge...