AIMC Topic: Polysomnography
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A comparative analysis of unsupervised machine-learning methods in PSG-related phenotyping.
Journal of sleep research
Oct 24, 2024
Obstructive sleep apnea is a heterogeneous sleep disorder with varying phenotypes. Several studies have already performed cluster analyses to discover various obstructive sleep apnea phenotypic clusters. However, the selection of the clustering metho...
IPCT-Net: Parallel information bottleneck modality fusion network for obstructive sleep apnea diagnosis.
Neural networks : the official journal of the International Neural Network Society
Oct 20, 2024
Obstructive sleep apnea (OSA) is a common sleep breathing disorder and timely diagnosis helps to avoid the serious medical expenses caused by related complications. Existing deep learning (DL)-based methods primarily focus on single-modal models, whi...
Machine-learning-based classification of obstructive sleep apnea using 19-channel sleep EEG data.
Sleep medicine
Sep 29, 2024
OBJECTIVE: This study aimed to investigate the neurophysiological effects of obstructive sleep apnea (OSA) using multi-channel sleep electroencephalography (EEG) through machine learning methods encompassing various analysis methodologies including p...
Classification of cyclic alternating patterns of sleep using EEG signals.
Sleep medicine
Sep 24, 2024
Cyclic alternating patterns (CAP) occur in electroencephalogram (EEG) signals during non-rapid eye movement sleep. The analysis of CAP can offer insights into various sleep disorders. The first step is the identification of phases A and B for the CAP...
An enzyme-inspired specificity in deep learning model for sleep stage classification using multi-channel PSG signals input: Separating training approach and its performance on cross-dataset validation for generalizability.
Computers in biology and medicine
Sep 20, 2024
Numerous automatic sleep stage classification systems have been developed, but none have become effective assistive tools for sleep technicians due to issues with generalization. Four key factors hinder the generalization of these models are instrume...
Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis.
Journal of medical Internet research
Sep 10, 2024
BACKGROUND: Early detection of sleep apnea, the health condition where airflow either ceases or decreases episodically during sleep, is crucial to initiate timely interventions and avoid complications. Wearable artificial intelligence (AI), the integ...
Construction and evaluation of a predictive model for the types of sleep respiratory events in patients with OSA based on hypoxic parameters.
Sleep & breathing = Schlaf & Atmung
Aug 29, 2024
OBJECTIVE: To explore the differences and associations of hypoxic parameters among distinct types of respiratory events in patients with obstructive sleep apnea (OSA) and to construct prediction models for the types of respiratory events based on hyp...
Developing probabilistic ensemble machine learning models for home-based sleep apnea screening using overnight SpO2 data at varying data granularity.
Sleep & breathing = Schlaf & Atmung
Aug 27, 2024
PURPOSE: This study aims to develop sleep apnea screening models with overnight SpO2 data, and to investigate the impact of the SpO2 data granularity on model performance.
Enhanced machine learning approaches for OSA patient screening: model development and validation study.
Scientific reports
Aug 26, 2024
Age, gender, body mass index (BMI), and mean heart rate during sleep were found to be risk factors for obstructive sleep apnea (OSA), and a variety of methods have been applied to predict the occurrence of OSA. This study aimed to develop and evaluat...
Automatic prediction of obstructive sleep apnea in patients with temporomandibular disorder based on multidata and machine learning.
Scientific reports
Aug 21, 2024
Obstructive sleep apnea (OSA) is closely associated with the development and chronicity of temporomandibular disorder (TMD). Given the intricate pathophysiology of both OSA and TMD, comprehensive diagnostic approaches are crucial. This study aimed to...
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