A review of automated sleep disorder detection

S Xu, O Faust, S Seoni, S Chakraborty… - Computers in Biology …, 2022 - Elsevier
Automated sleep disorder detection is challenging because physiological symptoms can
vary widely. These variations make it difficult to create effective sleep disorder detection …

Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works

P Moridian, A Shoeibi, M Khodatars… - … : Data Mining and …, 2022 - Wiley Online Library
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while sleeping. This reduction in …

Development of an artificial intelligence-based breast cancer detection model by combining mammograms and medical health records

NTH Trang, KQ Long, PL An, TN Dang - Diagnostics, 2023 - mdpi.com
Background: Artificial intelligence (AI)-based computational models that analyze breast
cancer have been developed for decades. The present study was implemented to …

A 2D convolutional neural network to detect sleep apnea in children using airflow and oximetry

J Jiménez-García, M García, GC Gutiérrez-Tobal… - Computers in Biology …, 2022 - Elsevier
The gold standard approach to diagnose obstructive sleep apnea (OSA) in children is
overnight in-lab polysomnography (PSG), which is labor-intensive for clinicians and onerous …

[Retracted] A Comprehensive Review: Computational Models for Obstructive Sleep Apnea Detection in Biomedical Applications

ES JeyaJothi, J Anitha, S Rani… - BioMed research …, 2022 - Wiley Online Library
Obstructive sleep apnea (OSA) is a sleep disorder characterized by periodic episodes of
partial or complete upper airway obstruction caused by narrowing or collapse of the …

Application of artificial intelligence in the diagnosis of sleep apnea

G Bazoukis, SC Bollepalli, CT Chung, X Li… - Journal of Clinical …, 2023 - jcsm.aasm.org
Study Objectives: Machine learning (ML) models have been employed in the setting of sleep
disorders. This review aims to summarize the existing data about the role of ML techniques …

Is it useful to use computerized tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without …

O Eroğlu, Y Eroğlu, M Yıldırım, T Karlıdag… - American Journal of …, 2022 - Elsevier
Objective Cholesteatoma is an aggressive form of chronic otitis media (COM). For this
reason, it is important to distinguish between COM with and without cholesteatoma. In this …

[HTML][HTML] An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals

J Jiménez-García, M García, GC Gutiérrez-Tobal… - … Signal Processing and …, 2024 - Elsevier
Deep-learning algorithms have been proposed to analyze overnight airflow (AF) and
oximetry (SpO 2) signals to simplify the diagnosis of pediatric obstructive sleep apnea …

A deep learning framework for automatic sleep apnea classification based on empirical mode decomposition derived from single-lead electrocardiogram

F Setiawan, CW Lin - Life, 2022 - mdpi.com
Background: Although polysomnography (PSG) is a gold standard tool for diagnosing sleep
apnea (SA), it can reduce the patient's sleep quality by the placement of several disturbing …

A wearable device for at-home obstructive sleep apnea assessment: State-of-the-art and research challenges

NT Tran, HN Tran, AT Mai - Frontiers in neurology, 2023 - frontiersin.org
In the last 3 years, almost all medical resources have been reserved for the screening and
treatment of patients with coronavirus disease (COVID-19). Due to a shortage of medical …