Sleep Disorders

Sleep Disorders

Latest AI and machine learning research in sleep disorders for healthcare professionals.

2,814 articles

Neurology Subcategories: Autism Dementia Head Trauma Parkinson's Disease Seizures Sleep Disorders

Showing 421-441 of 2,814 articles

A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.

Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies...

(9)

Jul 2023 38082822

Enhancing OSA Assessment with Explainable AI.

Explainable Artificial Intelligence (xAI) is a rapidly growing field that focuses on making deep lea...

Jul 2023 38083271

Identification of Sleep Patterns via Clustering of Hypnodensities.

Sleep patterns vary widely between individuals. We explore methods for identifying populations exhib...

(1)

Jul 2023 38083670

[Single-channel electroencephalogram signal used for sleep state recognition based on one-dimensional width kernel convolutional neural networks and long-short-term memory networks].

Aiming at the problem that the unbalanced distribution of data in sleep electroencephalogram(EEG) si...

(2)

Dec 2022 36575077

Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings.

Nowadays, high amounts of data can be acquired in various applications, spurring the need for interp...

Jul 2022 36086087

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

Sleep state classification is essential for managing and comprehending sleep patterns, and it is usu...

(1)

Jul 2022 36086100

[Discrimination of Chin Electromyography in REM Sleep Behavior Disorder Using Deep Learning].

OBJECTIVE: The confirmation of abnormal behavior during video monitoring in polysomnography (PSG) an...

Jan 2022 35314576

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea.

The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) t...

Jan 2022 36217082

Application of Machine Learning to Sleep Stage Classification.

Sleep studies are imperative to recapitulate phenotypes associated with sleep loss and uncover mecha...

(2)

Dec 2021 36313065

The quantification and clinical analysis of depression and anxiety in patients undergoing Da Vinci robot-assisted radical gastrectomy and open radical gastrectomy.

The purpose of paper is to investigate the depression and anxiety as well as independent influential...

Nov 2021 34596103

Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram.

Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. Most cases of ...

Nov 2021 34892516

Large-scale assessment of consistency in sleep stage scoring rules among multiple sleep centers using an interpretable machine learning algorithm.

STUDY OBJECTIVES: Polysomnography is the gold standard in identifying sleep stages; however, there a...

Feb 2021 32964831

Deep learning applied to polysomnography to predict blood pressure in obstructive sleep apnea and obesity hypoventilation: a proof-of-concept study.

STUDY OBJECTIVES: Nocturnal blood pressure (BP) profile shows characteristic abnormalities in OSA, n...

Oct 2020 32484157

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

Network physiology describes the human body as a complex network of interacting organ systems. It ha...

(1)

Dec 2019 31893662

Neurology

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A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.

Enhancing OSA Assessment with Explainable AI.

Identification of Sleep Patterns via Clustering of Hypnodensities.

[Single-channel electroencephalogram signal used for sleep state recognition based on one-dimensional width kernel convolutional neural networks and long-short-term memory networks].

Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings.

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

[Discrimination of Chin Electromyography in REM Sleep Behavior Disorder Using Deep Learning].

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea.

Application of Machine Learning to Sleep Stage Classification.

The quantification and clinical analysis of depression and anxiety in patients undergoing Da Vinci robot-assisted radical gastrectomy and open radical gastrectomy.

Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram.

Large-scale assessment of consistency in sleep stage scoring rules among multiple sleep centers using an interpretable machine learning algorithm.

Deep learning applied to polysomnography to predict blood pressure in obstructive sleep apnea and obesity hypoventilation: a proof-of-concept study.

Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample.

Deep transfer learning for improving single-EEG arousal detection.

Predicting Age with Deep Neural Networks from Polysomnograms.

Automatic Detection of Respiratory Effort Related Arousals With Deep Neural Networks From Polysomnographic Recordings.

Temporal dependency in automatic sleep scoring via deep learning based architectures: An empirical study.

Artificial intelligence in sleep medicine: an American Academy of Sleep Medicine position statement.

Artificial intelligence in sleep medicine: background and implications for clinicians.

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

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