[HTML][HTML] COVID-19 detection using chest X-ray images based on a developed deep neural network
Aim Currently, a new coronavirus called COVID-19 is the biggest challenge of the human at
21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities …
21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities …
Deep neural networks–based damage detection using vibration signals of finite element model and real intact state: An evaluation via a lab-scale offshore jacket …
Structural health monitoring of mechanical systems is essential to avoid their catastrophic
failure. In this article, an effective deep neural network is developed for extracting the …
failure. In this article, an effective deep neural network is developed for extracting the …
Developing a deep neural network for driver fatigue detection using EEG signals based on compressed sensing
In recent years, driver fatigue has become one of the main causes of road accidents. As a
result, fatigue detection systems have been developed to warn drivers, and, among the …
result, fatigue detection systems have been developed to warn drivers, and, among the …
Developing deep neural network for damage detection of beam-like structures using dynamic response based on FE model and real healthy state
Abstract Fundamentally, Structural Health Monitoring (SHM) of mechanical systems is
essential to avoid their catastrophic failure. The first key contribution of this paper is …
essential to avoid their catastrophic failure. The first key contribution of this paper is …
Performance analysis of machine learning algorithms on automated sleep staging feature sets
S Satapathy, D Loganathan… - CAAI Transactions …, 2021 - Wiley Online Library
With the speeding up of social activities, rapid changes in lifestyles, and an increase in the
pressure in professional fields, people are suffering from several types of sleep‐related …
pressure in professional fields, people are suffering from several types of sleep‐related …
Deep learning application to clinical decision support system in sleep stage classification
Recently, deep learning for automated sleep stage classification has been introduced with
promising results. However, as many challenges impede their routine application, automatic …
promising results. However, as many challenges impede their routine application, automatic …
[HTML][HTML] Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images
S Sheykhivand, Z Mousavi, S Mojtahedi… - Alexandria Engineering …, 2021 - Elsevier
Abstract The novel coronavirus (COVID-19) could be described as the greatest human
challenge of the 21st century. The development and transmission of the disease have …
challenge of the 21st century. The development and transmission of the disease have …
Automatic sleep scoring: A deep learning architecture for multi-modality time series
Background Sleep scoring is an essential but time-consuming process, and therefore
automatic sleep scoring is crucial and urgent to help address the growing unmet needs for …
automatic sleep scoring is crucial and urgent to help address the growing unmet needs for …
Symbiotic organisms search algorithm using random walk and adaptive Cauchy mutation on the feature selection of sleep staging
F Miao, L Yao, X Zhao - Expert Systems with Applications, 2021 - Elsevier
Sleep staging can objectively evaluate sleep quality to effectively assist in preventing and
diagnosing sleep disorder. Because of the multi-channel and multi-model characteristics of …
diagnosing sleep disorder. Because of the multi-channel and multi-model characteristics of …
PET-validated EEG-machine learning algorithm predicts brain amyloid pathology in pre-dementia Alzheimer's disease
NH Kim, U Park, DW Yang, SH Choi, YC Youn… - Scientific Reports, 2023 - nature.com
Developing reliable biomarkers is important for screening Alzheimer's disease (AD) and
monitoring its progression. Although EEG is non-invasive direct measurement of brain …
monitoring its progression. Although EEG is non-invasive direct measurement of brain …