AIMC Topic: Sleep Wake Disorders
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Machine and Deep Learning in Molecular and Genetic Aspects of Sleep Research.
Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics
Apr 7, 2021
Epidemiological sleep research strives to identify the interactions and causal mechanisms by which sleep affects human health, and to design intervention strategies for improving sleep throughout the lifespan. These goals can be advanced by further f...
Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning.
Sensors (Basel, Switzerland)
May 2, 2020
Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) hav...
Deep learning approaches for sleep disorder prediction in an asthma cohort.
The Journal of asthma : official journal of the Association for the Care of Asthma
Mar 18, 2020
OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower productivity. This study examined 1 million samples included in the Taiwan National Health Insurance ...
Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.
Artificial intelligence in medicine
Jan 21, 2020
Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, lo...
Sleep heart rate variability assists the automatic prediction of long-term cardiovascular outcomes.
Sleep medicine
Dec 16, 2019
OBJECTIVE: We aimed to investigate the association between sleep HRV and long-term cardiovascular disease (CVD) outcomes, and further explore whether HRV features can assist the automatic CVD prediction.
Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.
Computer methods and programs in biomedicine
Sep 27, 2019
BACKGROUND AND OBJECTIVE: In recent years, several automatic sleep stage classification methods based on convolutional neural networks (CNN) by learning hierarchical feature representation automatically from raw EEG data have been proposed. However, ...
Sleep Stages
Reproducibility of Results
Sleep
Adult
Calibration
Humans
Sensitivity and Specificity
Electroencephalography
Polysomnography
Neural Networks, Computer
Time Factors
Male
Signal Processing, Computer-Assisted
Sleep Wake Disorders
Machine Learning
Electrocardiography
Sleep Apnea, Obstructive
Algorithms
Databases, Factual
Automated sleep scoring: A review of the latest approaches.
Sleep medicine reviews
Aug 9, 2019
Clinical sleep scoring involves a tedious visual review of overnight polysomnograms by a human expert, according to official standards. It could appear then a suitable task for modern artificial intelligence algorithms. Indeed, machine learning algor...
Using heart rate profiles during sleep as a biomarker of depression.
BMC psychiatry
Jun 7, 2019
BACKGROUND: Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may provide new information about physiological sleep signatures of depression. This study assessed the validity of an algorithm using patterns of heart ...
SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach.
PloS one
May 7, 2019
Electroencephalogram (EEG) is a common base signal used to monitor brain activities and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep experts and is limited by inter-rater reliability. In this paper, we propo...
A deep learning-based decision support system for diagnosis of OSAS using PTT signals.
Medical hypotheses
Mar 27, 2019
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...
Electromyography
Neural Networks, Computer
Sleep Apnea, Obstructive
Healthy Volunteers
Adult
Algorithms
Humans
Middle Aged
Carbon Dioxide
Electrocardiography
Motivation
Male
Female
Heart Rate
Deep Learning
Support Vector Machine
Aged
Medical Informatics
Decision Support Systems, Clinical
Electroencephalography
Sleep Wake Disorders
Signal Processing, Computer-Assisted
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