AIMC Topic: Sleep Apnea, Obstructive

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Machine learning for OSA diagnosis: advancing automated and accurate methods.

Minerva dental and oral science Jan 19, 2024
Sleep Apnea, Obstructive Humans Machine Learning
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Automatic prediction of obstructive sleep apnea event using deep learning algorithm based on ECG and thoracic movement signals.

Acta oto-laryngologica Jan 19, 2024
BACKGROUND: Obstructive sleep apnea (OSA) is a sleeping disorder that can cause multiple complications.
Sleep Apnea, Obstructive Deep Learning Electrocardiography Humans Algorithms Retrospective Studies
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Deep learning of sleep apnea-hypopnea events for accurate classification of obstructive sleep apnea and determination of clinical severity.

Sleep medicine Jan 11, 2024
BACKGROUND: /Objective: Automatic apnea/hypopnea events classification, crucial for clinical applications, often faces challenges, particularly in hypopnea detection. This study aimed to evaluate the efficiency of a combined approach using nasal resp...
Humans Sleep Apnea, Obstructive Sleep Polysomnography Deep Learning Sleep Apnea Syndromes
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A machine learning model to predict the risk of depression in US adults with obstructive sleep apnea hypopnea syndrome: a cross-sectional study.

Frontiers in public health Jan 8, 2024
OBJECTIVE: Depression is very common and harmful in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). It is necessary to screen OSAHS patients for depression early. However, there are no validated tools to assess the likelihood of depr...
Depression Adult Syndrome Humans Nutrition Surveys Cross-Sectional Studies Sleep Apnea, Obstructive Machine Learning
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The effect and exploration of continuous positive pressure ventilation combined with upper limb robot training on upper limb function in stroke patients with OSAHS.

Panminerva medica Nov 30, 2023
Recovery of Function Robotics Stroke Combined Modality Therapy Middle Aged Treatment Outcome Aged Male Humans Continuous Positive Airway Pressure Female Stroke Rehabilitation Sleep Apnea, Obstructive Upper Extremity
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Wavelet transform and deep learning-based obstructive sleep apnea detection from single-lead ECG signals.

Physical and engineering sciences in medicine Nov 20, 2023
Sleep apnea is a common sleep disorder. Traditional testing and diagnosis heavily rely on the expertise of physicians, as well as analysis and statistical interpretation of extensive sleep testing data, resulting in time-consuming and labor-intensive...
Sleep Apnea Syndromes Sleep Apnea, Obstructive Wavelet Analysis Deep Learning Electrocardiography Humans
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Sleep Apnea Prediction Using Deep Learning.

IEEE journal of biomedical and health informatics Nov 7, 2023
Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods have been proposed to automatically detect OSA events, but little work has focused on predicting su...
Sleep Apnea, Obstructive Sleep Deep Learning Sleep Apnea Syndromes Respiration Humans
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Semi-Supervised Learning for Low-Cost Personalized Obstructive Sleep Apnea Detection Using Unsupervised Deep Learning and Single-Lead Electrocardiogram.

IEEE journal of biomedical and health informatics Nov 7, 2023
OBJECTIVE: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that can lead to a wide range of health issues if left untreated. This study aims to address the lack of research on personalized models for single-lead electrocard...
Deep Learning Electrocardiography Supervised Machine Learning Humans Sleep Apnea, Obstructive Respiration
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Screening obstructive sleep apnea patients via deep learning of knowledge distillation in the lateral cephalogram.

Scientific reports Oct 18, 2023
The lateral cephalogram in orthodontics is a valuable screening tool on undetected obstructive sleep apnea (OSA), which can lead to consequences of severe systematic disease. We hypothesized that a deep learning-based classifier might be able to diff...
Polysomnography Humans Deep Learning Radiography Sleep Apnea, Obstructive ROC Curve
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Developing a deep learning model for sleep stage prediction in obstructive sleep apnea cohort using 60 GHz frequency-modulated continuous-wave radar.

Journal of sleep research Sep 26, 2023
Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In ...
Sleep Apnea, Obstructive Sleep Humans Deep Learning Radar Sleep Stages
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