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Sleep Initiation and Maintenance Disorders

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Insomnia disorder diagnosed by resting-state fMRI-based SVM classifier.

Sleep medicine
BACKGROUND: The main classification systems of sleep disorders are based on the subjective self-reported criteria. Objective measures are essential to characterize the nocturnal sleep disturbance, identify daytime impairment, and determine the course...

The effects of a sleep robot intervention on sleep, depression and anxiety in adults with insomnia - Study protocol of a randomized waitlist-controlled trial.

Contemporary clinical trials
Insomnia is a common sleep disorder characterized by difficulties initiating sleep, maintaining sleep and/or early-morning awakenings. Hyperarousal is a common causal and maintaining factor in insomnia models. Different techniques to decrease arousal...

Multitask fMRI and machine learning approach improve prediction of differential brain activity pattern in patients with insomnia disorder.

Scientific reports
We investigated the differential spatial covariance pattern of blood oxygen level-dependent (BOLD) responses to single-task and multitask functional magnetic resonance imaging (fMRI) between patients with psychophysiological insomnia (PI) and healthy...

Revisiting the value of polysomnographic data in insomnia: more than meets the eye.

Sleep medicine
BACKGROUND: Polysomnography (PSG) is not recommended as a diagnostic tool in insomnia. However, this consensual approach might be tempered in the light of two ongoing transformations in sleep research: big data and artificial intelligence (AI).

Prediction of lithium response using clinical data.

Acta psychiatrica Scandinavica
OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical ma...

Network physiology in insomnia patients: Assessment of relevant changes in network topology with interpretable machine learning models.

Chaos (Woodbury, N.Y.)
Network physiology describes the human body as a complex network of interacting organ systems. It has been applied successfully to determine topological changes in different sleep stages. However, the number of network links can quickly grow above th...

Extracting health-related causality from twitter messages using natural language processing.

BMC medical informatics and decision making
BACKGROUND: Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encountered in our daily lives. In...

A Two Stage Approach for the Automatic Detection of Insomnia.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Chronic insomnia can significantly impair an individual's quality of life leading to a high societal cost. Unfortunately, limited automated tools exist that can assist clinicians in the timely detection of insomnia. In this paper, we propose a two st...

[Effect of Acupuncture at Points in Heel Vessel for Circadian Genes of 1 and 2 mRNAs in the Suprachiasmatic Nucleus in Insomnia Rats].

Zhen ci yan jiu = Acupuncture research
OBJECTIVE: To investigate the influence and mechanism of acupuncture at the points in Heel Vessel for the circadian clock genes of Period () 1 and 2 mRNAs in the suprachiasmatic nucleus (SCN) in insomnia rats.