AIMC Topic: Sleep

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AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning.

Artificial intelligence in medicine Jul 2, 2021
Obstructive Sleep Apnea Syndrome (OSAS) is the most common sleep-related breathing disorder. It is caused by an increased upper airway resistance during sleep, which determines episodes of partial or complete interruption of airflow. The detection an...
Humans Deep Learning Vital Signs Polysomnography Sleep Apnea, Obstructive Sleep
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Automated scoring of pre-REM sleep in mice with deep learning.

Scientific reports Jun 10, 2021
Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accurac...
Sleep Stages Mice Sleep, REM Animals Algorithms Models, Theoretical Deep Learning Sleep Polysomnography
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Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning.

IEEE transactions on bio-medical engineering May 21, 2021
BACKGROUND: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues....
Humans Sleep Polysomnography Neural Networks, Computer Machine Learning Sleep Stages
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A CNN identified by reinforcement learning-based optimization framework for EEG-based state evaluation.

Journal of neural engineering May 18, 2021
Electroencephalogram (EEG) data, as a kind of complex time-series, is one of the most widely-used information measurements for evaluating human psychophysiological states. Recently, numerous works applied deep learning techniques, especially the conv...
Sleep Sleep Stages Algorithms Electroencephalography Humans Neural Networks, Computer
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A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data.

Sensors (Basel, Switzerland) May 11, 2021
Sleep disturbances are common in Alzheimer's disease and other neurodegenerative disorders, and together represent a potential therapeutic target for disease modification. A major barrier for studying sleep in patients with dementia is the requiremen...
Sleep Stages Sleep Polysomnography Deep Learning Electroencephalography Humans
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A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video.

IEEE journal of biomedical and health informatics May 11, 2021
Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake pattern, which functions as an essential indicator of neurophysiological organization in the neonatal period, has profound meaning in the prediction of cognitive d...
Facial Expression Support Vector Machine Sleep Humans Neural Networks, Computer Infant, Newborn China
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Activation patterns of interictal epileptiform discharges in relation to sleep and seizures: An artificial intelligence driven data analysis.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology May 8, 2021
OBJECTIVE: To quantify effects of sleep and seizures on the rate of interictal epileptiform discharges (IED) and to classify patients with epilepsy based on IED activation patterns.
Humans Circadian Rhythm Artificial Intelligence Sleep Epilepsy Data Analysis Seizures Retrospective Studies Electroencephalography
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An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society May 5, 2021
Automatic sleep stage mymargin classification is of great importance to measure sleep quality. In this paper, we propose a novel attention-based deep learning architecture called AttnSleep to classify sleep stages using single channel EEG signals. Th...
Sleep Stages Electroencephalography Sleep Neural Networks, Computer Deep Learning
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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...
Sleep Humans Sleep Wake Disorders Machine Learning Deep Learning
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Hybrid manifold-deep convolutional neural network for sleep staging.

Methods (San Diego, Calif.) Feb 24, 2021
Analysis of electroencephalogram (EEG) is a crucial diagnostic criterion for many sleep disorders, of which sleep staging is an important component. Manual stage classification is a labor-intensive process and usually suffered from many subjective fa...
Humans Sleep Stages Electroencephalography Neural Networks, Computer Sleep
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