The role of artificial neural network and machine learning in utilizing spatial information

A Goel, AK Goel, A Kumar - Spatial Information Research, 2023 - Springer
In this age of the fourth industrial revolution 4.0, the digital world has a plethora of data,
including the internet of things, mobile, cybersecurity, social media, forecasts, health data …

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 …

[HTML][HTML] Deep neural network technique for automated detection of ADHD and CD using ECG signal

HW Loh, CP Ooi, SL Oh, PD Barua, YR Tan… - Computer methods and …, 2023 - Elsevier
Abstract Background and objective Attention Deficit Hyperactivity problem (ADHD) is a
common neurodevelopment problem in children and adolescents that can lead to long-term …

A deep learning approach for atrial fibrillation classification using multi-feature time series data from ecg and ppg

B Aldughayfiq, F Ashfaq, NZ Jhanjhi, M Humayun - Diagnostics, 2023 - mdpi.com
Atrial fibrillation is a prevalent cardiac arrhythmia that poses significant health risks to
patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and …

Ensemble computational intelligent for insomnia sleep stage detection via the sleep ECG signal

P Tripathi, MA Ansari, TK Gandhi, R Mehrotra… - IEEE …, 2022 - ieeexplore.ieee.org
Insomnia is a common sleep disorder in which patients cannot sleep properly. Accurate
detection of insomnia disorder is a crucial step for mental disease analysis in the early …

Portable evaluation of obstructive sleep apnea in adults: A systematic review

YH Khor, SW Khung, WR Ruehland, Y Jiao, J Lew… - Sleep Medicine …, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a significant healthcare burden affecting approximately
one billion people worldwide. The prevalence of OSA is rising with the ongoing obesity …

RAFNet: Restricted attention fusion network for sleep apnea detection

Y Chen, H Yue, R Zou, W Lei, W Ma, X Fan - Neural Networks, 2023 - Elsevier
Sleep apnea (SA) is a common sleep-related breathing disorder, which would lead to
damage of multiple systemic organs or even sudden death. In clinical practice, portable …

Dominant noise-aided EMD (DEMD): Extending empirical mode decomposition for noise reduction by incorporating dominant noise and deep classification

Z Shamaee, M Mivehchy - Biomedical Signal Processing and Control, 2023 - Elsevier
Biomedical signals are frequently contaminated by colored noise; consequently, noise
recognition and reduction are critical to biomedical systems. Conventional techniques have …

Robust method for screening sleep apnea with single-lead ecg using deep residual network: evaluation with open database and patch-type wearable device data

M Yeo, H Byun, J Lee, J Byun, HY Rhee… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
This paper proposes a robust method to screen patients with sleep apnea syndrome (SAS)
using a single-lead electrocardiogram (ECG). This method consists of minute-by-minute …

Multi-task feature fusion network for Obstructive Sleep Apnea detection using single-lead ECG signal

K Cao, X Lv - Measurement, 2022 - Elsevier
Efficient daily monitoring of Obstructive Sleep Apnea (OSA) and timely implementation of
treatment is one of the important measures to ensure human health and sleep quality …