2.7k citations · 3.7k across the 13 of their papers we have counts for
13 papers
Explainable Artificial Intelligence for Drug Discovery and Development -- A Comprehensive Survey
Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain +5
The field of drug discovery has experienced a remarkable transformation with the advent of artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI…
A Hybrid Deep Spatio-Temporal Attention-Based Model for Parkinson's Disease Diagnosis Using Resting State EEG Signals
Niloufar Delfan, Mohammadreza Shahsavari, Sadiq Hussain +2
Parkinson's disease (PD), a severe and progressive neurological illness, affects millions of individuals worldwide. For effective treatment and management of PD, an accurate and ea…
BERT-Deep CNN: State-of-the-Art for Sentiment Analysis of COVID-19 Tweets
Javad Hassannataj Joloudari, Sadiq Hussain, Mohammad Ali Nematollahi +5
The free flow of information has been accelerated by the rapid development of social media technology. There has been a significant social and psychological impact on the populatio…
UncertaintyFuseNet: Robust Uncertainty-aware Hierarchical Feature Fusion Model with Ensemble Monte Carlo Dropout for COVID-19 Detection
Moloud Abdar, Soorena Salari, Sina Qahremani +7
The COVID-19 (Coronavirus disease 2019) pandemic has become a major global threat to human health and well-being. Thus, the development of computer-aided detection (CAD) systems th…
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…
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.…
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar, Farhad Pourpanah, Sadiq Hussain +9
Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes. It can be applied to solve a variety of r…
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…
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…