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

Showing 190-210 of 2,783 articles

A novel deep learning model for obstructive sleep apnea diagnosis: hybrid CNN-Transformer approach for radar-based detection of apnea-hypopnea events.

STUDY OBJECTIVES: The demand for cost-effective and accessible alternatives to polysomnography (PSG)...

Dec 2024 PMID: 39115132

Combining a wireless radar sleep monitoring device with deep machine learning techniques to assess obstructive sleep apnea severity.

STUDY OBJECTIVES: The gold standard for diagnosing obstructive sleep apnea (OSA) is polysomnography ...

Aug 2024 PMID: 38546033

[Constructing a cataplexy face prediction model for narcolepsy type 1 based on ResNet-18].

To establish a prediction model for the identifying of cataplexy facial features based on clinical ...

Jul 2024 PMID: 38978380

Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models.

The incidence of clinically undiagnosed obstructive sleep apnea (OSA) is high among the general pop...

Jul 2024 PMID: 38471111

Predicting Sleep Quality via Unsupervised Learning of Cardiac Activity.

While highly important for a person's mood, productivity, and physical performance, perceived sleep ...

Jul 2024 PMID: 40039685

Sleep structure discriminates patients with isolated REM sleep behavior disorder: a deep learning approach.

Rapid eye movement (REM) sleep behavior disorder (RBD) is a disorder characterized by increased musc...

Jul 2024 PMID: 40039123

Ensemble Learning Approaches for Automatic Detection of Chronic Kidney Disease Stages during Sleep.

This study investigates the use of ensemble learning methods for the automatic detection of chronic ...

Jul 2024 PMID: 40039046

Heterogeneous Effects of Continuous Positive Airway Pressure in Non-Sleepy Obstructive Sleep Apnea on Cardiovascular Disease Outcomes: Machine Learning Analysis of the ISAACC Trial (ECSACT Study).

Randomized controlled trials of continuous positive airway pressure (CPAP) therapy for cardiovascul...

Jul 2024 PMID: 38358332

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

STUDY OBJECTIVES: The standard of care for military personnel with insomnia is cognitive behavioral ...

Jun 2024 PMID: 38300822

Evaluating insomnia queries from an artificial intelligence chatbot for patient education.

STUDY OBJECTIVES: We evaluated the accuracy of ChatGPT in addressing insomnia-related queries for pa...

Apr 2024 PMID: 38217478

Standardized image-based polysomnography database and deep learning algorithm for sleep-stage classification.

STUDY OBJECTIVES: Polysomnography (PSG) scoring is labor-intensive, subjective, and often ambiguous....

Dec 2023 PMID: 37703391

Identification of Sleep Patterns via Clustering of Hypnodensities.

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

Jul 2023 PMID: 38083670

Enhancing OSA Assessment with Explainable AI.

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

Jul 2023 PMID: 38083271

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...

Jul 2023 PMID: 38082822

[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...

Dec 2022 PMID: 36575077

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 PMID: 34892516

Neurology

Browse Specialties

A novel deep learning model for obstructive sleep apnea diagnosis: hybrid CNN-Transformer approach for radar-based detection of apnea-hypopnea events.

Combining a wireless radar sleep monitoring device with deep machine learning techniques to assess obstructive sleep apnea severity.

[Constructing a cataplexy face prediction model for narcolepsy type 1 based on ResNet-18].

Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models.

Predicting Sleep Quality via Unsupervised Learning of Cardiac Activity.

Sleep structure discriminates patients with isolated REM sleep behavior disorder: a deep learning approach.

Ensemble Learning Approaches for Automatic Detection of Chronic Kidney Disease Stages during Sleep.

Heterogeneous Effects of Continuous Positive Airway Pressure in Non-Sleepy Obstructive Sleep Apnea on Cardiovascular Disease Outcomes: Machine Learning Analysis of the ISAACC Trial (ECSACT Study).

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

Evaluating insomnia queries from an artificial intelligence chatbot for patient education.

Standardized image-based polysomnography database and deep learning algorithm for sleep-stage classification.

Identification of Sleep Patterns via Clustering of Hypnodensities.

Enhancing OSA Assessment with Explainable AI.

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.

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

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

Self-Organizing Maps for Contrastive Embeddings of Sleep Recordings.

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

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

Application of Machine Learning to Sleep Stage Classification.

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

Browse Specialties