463 citations · 1.9k across the 23 of their papers we have counts for
24 papers
Empowering Precision Medicine: AI-Driven Schizophrenia Diagnosis via EEG Signals: A Comprehensive Review from 2002-2023
Mahboobeh Jafari, Delaram Sadeghi, Afshin Shoeibi +6
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional, and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack o…
A Brief Review of Explainable Artificial Intelligence in Healthcare
Zahra Sadeghi, Roohallah Alizadehsani, Mehmet Akif Cifci +13
XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-sta…
Automated Diagnosis of Cardiovascular Diseases from Cardiac Magnetic Resonance Imaging Using Deep Learning Models: A Review
Mahboobeh Jafari, Afshin Shoeibi, Marjane Khodatars +11
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality globally. CVDs appear with minor symptoms and progressively get worse. The majori…
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence
Mahboobeh Jafari, Afshin Shoeibi, Navid Ghassemi +9
Myocarditis is a significant cardiovascular disease (CVD) that poses a threat to the health of many individuals by causing damage to the myocardium. The occurrence of microbes and…
Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
Parisa Moridian, Navid Ghassemi, Mahboobeh Jafari +11
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and symptoms that appear in early childhood. ASD is also associated with communication deficits a…
Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression
Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars +7
Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and…
Accurate Prediction Using Triangular Type-2 Fuzzy Linear Regression
Assef Zare, Afshin Shoeibi, Narges Shafaei +4
Many works have been done to handle the uncertainties in the data using type 1 fuzzy regression. Few type 2 fuzzy regression works used interval type 2 for indeterminate modeling u…
What happens in Face during a facial expression? Using data mining techniques to analyze facial expression motion vectors
Mohamad Roshanzamir, Roohallah Alizadehsani, Mahdi Roshanzamir +4
One of the most common problems encountered in human-computer interaction is automatic facial expression recognition. Although it is easy for human observer to recognize facial exp…
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies
Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars +7
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 electr…
Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models
Afshin Shoeibi, Delaram Sadeghi, Parisa Moridian +8
Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals in the brain, the function of some brain regions is out of balance, leading to the lack o…
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works
Afshin Shoeibi, Parisa Moridian, Marjane Khodatars +9
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements.…
Applications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari +9
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. I…
Automatic Diagnosis of COVID-19 from CT Images using CycleGAN and Transfer Learning
Navid Ghassemi, Afshin Shoeibi, Marjane Khodatars +5
The outbreak of the corona virus disease (COVID-19) has changed the lives of most people on Earth. Given the high prevalence of this disease, its correct diagnosis in order to quar…
Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods
Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani +9
The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs…
Combining a Convolutional Neural Network with Autoencoders to Predict the Survival Chance of COVID-19 Patients
Fahime Khozeimeh, Danial Sharifrazi, Navid Hoseini Izadi +10
COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classificati…
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works
Delaram Sadeghi, Afshin Shoeibi, Navid Ghassemi +9
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, pe…
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir +13
The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to pre…
Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data
Roohallah Alizadehsani, Danial Sharifrazi, Navid Hoseini Izadi +11
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.…
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991-2020)
Roohallah Alizadehsani, Mohamad Roshanzamir, Sadiq Hussain +12
Understanding data and reaching valid conclusions are of paramount importance in the present era of big data. Machine learning and probability theory methods have widespread applic…
Development of novel algorithm to visualize blood vessels on 3D ultrasound images during liver surgery
Fatemeh Salehihafshejani, Alireza Ahmadian, Afshin Shoeibi +5
Volume visualization is a method that displays three-dimensional (3D) data in two-dimensional (2D) space. Using 3D datasets instead of 2D traditional images improves the visualizat…
Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari +12
Coronavirus, or COVID-19, is a hazardous disease that has endangered the health of many people around the world by directly affecting the lungs. COVID-19 is a medium-sized, coated…
Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review
Marjane Khodatars, Afshin Shoeibi, Delaram Sadeghi +12
Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) techniques…
Epileptic Seizures Detection Using Deep Learning Techniques: A Review
Afshin Shoeibi, Marjane Khodatars, Navid Ghassemi +14
A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial…
Material Recognition for Automated Progress Monitoring using Deep Learning Methods
Hadi Mahami, Navid Ghassemi, Mohammad Tayarani Darbandy +7
Recent advancements in Artificial intelligence, especially deep learning, has changed many fields irreversibly by introducing state of the art methods for automation. Construction…