A comprehensive survey on design and application of autoencoder in deep learning
Autoencoder is an unsupervised learning model, which can automatically learn data
features from a large number of samples and can act as a dimensionality reduction method …
features from a large number of samples and can act as a dimensionality reduction method …
Application of artificial intelligence in wearable devices: Opportunities and challenges
D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …
Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
Uncertainty-aware semi-supervised method using large unlabeled and limited labeled COVID-19 data
R Alizadehsani, D Sharifrazi, NH Izadi… - ACM Transactions on …, 2021 - dl.acm.org
The new coronavirus has caused more than one million deaths and continues to spread
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization
Coronavirus disease 2019 (COVID-19) is a highly contagious disease that has claimed the
lives of millions of people worldwide in the last 2 years. Because of the disease's rapid …
lives of millions of people worldwide in the last 2 years. Because of the disease's rapid …
Generative adversarial network based data augmentation for CNN based detection of Covid-19
Covid-19 has been a global concern since 2019, crippling the world economy and health.
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …
Densely attention mechanism based network for COVID-19 detection in chest X-rays
Automatic COVID-19 detection using chest X-ray (CXR) can play a vital part in large-scale
screening and epidemic control. However, the radiographic features of CXR have different …
screening and epidemic control. However, the radiographic features of CXR have different …
Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study
Background Diabetic mellitus (DM) and cardiovascular diseases (CVD) cause significant
healthcare burden globally and often co-exists. Current approaches often fail to identify …
healthcare burden globally and often co-exists. Current approaches often fail to identify …
Epileptic seizures detection in EEG signals using fusion handcrafted and deep learning features
Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …