User profiles for Afshin Shoeibi
Afshin ShoeibiResearcher, School of Computing, Macquarie University, Australia Verified email at mq.edu.au Cited by 3975 |
Deep neural network with generative adversarial networks pre-training for brain tumor classification based on MR images
In this paper, a new deep learning method for tumor classification in MR images is presented.
A deep neural network is first pre-trained as a discriminator in a generative adversarial …
A deep neural network is first pre-trained as a discriminator in a generative adversarial …
A comprehensive comparison of handcrafted features and convolutional autoencoders for epileptic seizures detection in EEG signals
Epilepsy, a brain disease generally associated with seizures, has tremendous effects on
people’s quality of life. Diagnosis of epileptic seizures is commonly performed on …
people’s quality of life. Diagnosis of epileptic seizures is commonly performed on …
[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. …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior, …
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior, …
Automated detection and forecasting of covid-19 using deep learning techniques: A review
In March 2020, the World Health Organization (WHO) declared COVID-19 a global epidemic,
caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real-time …
caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real-time …
Uncertainty-aware semi-supervised method using large unlabeled and limited labeled COVID-19 data
…, NH Izadi, JH Joloudari, A Shoeibi… - 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 severe. …
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe. …
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In order …
problems for people with a detrimental effect on the functioning of the nervous system. In order …
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022 - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
Risk factors prediction, clinical outcomes, and mortality in COVID‐19 patients
…, F Hasanzadeh, A Khosravi, A Shoeibi… - Journal of medical …, 2021 - Wiley Online Library
Preventing communicable diseases requires understanding the spread, epidemiology, clinical
features, progression, and prognosis of the disease. Early identification of risk factors and …
features, progression, and prognosis of the disease. Early identification of risk factors and …