Neurology

Sleep Disorders

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

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Enhancing automatic sleep stage classification with cerebellar EEG and machine learning techniques.

Sleep disorders have become a significant health concern in modern society. To investigate and diagn...

SiCRNN: A Siamese Approach for Sleep Apnea Identification via Tracheal Microphone Signals.

Sleep apnea syndrome (SAS) affects about 3-7% of the global population, but is often undiagnosed. It...

CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging.

Sleep staging is essential for sleep assessment and plays an important role in disease diagnosis, wh...

Artificial intelligence facial recognition of obstructive sleep apnea: a Bayesian meta-analysis.

PURPOSE: Conventional obstructive sleep apnea (OSA) diagnosis via polysomnography can be costly and ...

Comparison analysis between standard polysomnographic data and in-ear-electroencephalography signals: a preliminary study.

STUDY OBJECTIVES: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disor...

Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis.

BACKGROUND: Early detection of sleep apnea, the health condition where airflow either ceases or decr...

Twistable and Stretchable Nasal Patch for Monitoring Sleep-Related Breathing Disorders Based on a Stacking Ensemble Learning Model.

Obstructive sleep apnea syndrome disrupts sleep, destroys the homeostasis of biological systems such...

Enhanced machine learning approaches for OSA patient screening: model development and validation study.

Age, gender, body mass index (BMI), and mean heart rate during sleep were found to be risk factors f...

Automatic prediction of obstructive sleep apnea in patients with temporomandibular disorder based on multidata and machine learning.

Obstructive sleep apnea (OSA) is closely associated with the development and chronicity of temporoma...

Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold...

Study on the classification of sleep stages in EEG signals based on DoubleLinkSleepCLNet.

PURPOSE: The classification of sleep stages based on Electroencephalogram (EEG) changes has signific...

Improved sleep stage predictions by deep learning of photoplethysmogram and respiration patterns.

Sleep staging is a crucial tool for diagnosing and monitoring sleep disorders, but the standard clin...

Detection and severity assessment of obstructive sleep apnea according to deep learning of single-lead electrocardiogram signals.

Developing a convenient detection method is important for diagnosing and treating obstructive sleep ...

Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network.

Sleep quality is an essential parameter of a healthy human life, while sleep disorders such as sleep...

Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms.

Sleep disorders can have harmful consequences in both the short and long term. They can lead to atte...

Estimating the Severity of Obstructive Sleep Apnea Using ECG, Respiratory Effort and Neural Networks.

OBJECTIVE: wearable sensor technology has progressed significantly in the last decade, but its clini...

Comparison of model feature importance statistics to identify covariates that contribute most to model accuracy in prediction of insomnia.

IMPORTANCE: Sleep is critical to a person's physical and mental health and there is a need to create...

Exploring Heterogeneity in Cost-Effectiveness Using Machine Learning Methods: A Case Study Using the FIRST-ABC Trial.

OBJECTIVE: The aim of this study was to explore heterogeneity in the cost-effectiveness of high-flow...

Machine learning methods for adult OSAHS risk prediction.

BACKGROUND: Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause mul...

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