Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective
A Bandyopadhyay, C Goldstein - Sleep and Breathing, 2023 - Springer
Background The past few years have seen a rapid emergence of artificial intelligence (AI)-
enabled technology in the field of sleep medicine. AI refers to the capability of computer …
enabled technology in the field of sleep medicine. AI refers to the capability of computer …
A review of signals used in sleep analysis
A Roebuck, V Monasterio, E Gederi… - Physiological …, 2013 - iopscience.iop.org
This article presents a review of signals used for measuring physiology and activity during
sleep and techniques for extracting information from these signals. We examine both clinical …
sleep and techniques for extracting information from these signals. We examine both clinical …
An obstructive sleep apnea detection approach using a discriminative hidden Markov model from ECG signals
Obstructive sleep apnea (OSA) syndrome is a common sleep disorder suffered by an
increasing number of people worldwide. As an alternative to polysomnography (PSG) for …
increasing number of people worldwide. As an alternative to polysomnography (PSG) for …
Deep recurrent neural networks for automatic detection of sleep apnea from single channel respiration signals
Sleep apnea is a common sleep disorder that causes repeated breathing interruption during
sleep. The performance of automated apnea detection methods based on respiratory …
sleep. The performance of automated apnea detection methods based on respiratory …
Thirty years of artificial intelligence in medicine (AIME) conferences: A review of research themes
Background Over the past 30 years, the international conference on Artificial Intelligence in
MEdicine (AIME) has been organized at different venues across Europe every 2 years …
MEdicine (AIME) has been organized at different venues across Europe every 2 years …
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 …
disorders. This review aims to summarize the existing data about the role of ML techniques …
Cardiac sound murmurs classification with autoregressive spectral analysis and multi-support vector machine technique
S Choi, Z Jiang - Computers in biology and medicine, 2010 - Elsevier
In this paper, a novel cardiac sound spectral analysis method using the normalized
autoregressive power spectral density (NAR-PSD) curve with the support vector machine …
autoregressive power spectral density (NAR-PSD) curve with the support vector machine …
Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review
Objective: Sleep apnea (SA), a common sleep disorder, can significantly decrease the
quality of life, and is closely associated with major health risks such as cardiovascular …
quality of life, and is closely associated with major health risks such as cardiovascular …
Sleep apnea event detection from nasal airflow using convolutional neural networks
R Haidar, I Koprinska, B Jeffries - … 14–18, 2017, Proceedings, Part V 24, 2017 - Springer
Obstructive sleep apnea-hypopnea syndrome is a respiratory disorder characterized by
abnormal breathing patterns during sleep. It causes problems during sleep, including loud …
abnormal breathing patterns during sleep. It causes problems during sleep, including loud …
Classıfıcation of sleep apnea by using wavelet transform and artificial neural networks
This paper describes a new method to classify sleep apnea syndrome (SAS) by using
wavelet transforms and an artificial neural network (ANN). The network was trained and …
wavelet transforms and an artificial neural network (ANN). The network was trained and …