205 citations · 1.3k across the 19 of their papers we have counts for
20 papers
EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia
Francisco Jesus Martinez-Murcia, Andrés Ortiz, Juan Manuel Górriz +4
The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological difficulties of dyslexia are caused by an atypical oscillatory sampling at one or more temporal…
Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?
Francisco J. Martinez-Murcia, Juan M. Górriz, Javier Ramírez +1
Spatial and intensity normalization are nowadays a prerequisite for neuroimaging analysis. Influenced by voxel-wise and other univariate comparisons, where these corrections are ke…
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…
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…
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…
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…
Tiled sparse coding in eigenspaces for the COVID-19 diagnosis in chest X-ray images
Juan E. Arco, Andrés Ortiz, Javier Ramírez +1
The ongoing crisis of the COVID-19 (Coronavirus disease 2019) pandemic has changed the world. According to the World Health Organization (WHO), 4 million people have died due to th…
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…
Deep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization ability
Carmen Jiménez-Mesa, Javier Ramírez, John Suckling +5
Discriminative analysis in neuroimaging by means of deep/machine learning techniques is usually tested with validation techniques, whereas the associated statistical significance r…
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…
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 connection between the pattern classification problem and the General Linear Model for statistical inference
Juan Manuel Gorriz, SIPBA group, John Suckling
A connection between the General Linear Model (GLM) in combination with classical statistical inference and the machine learning (MLE)-based inference is described in this paper. F…
Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images
Juan E. Arco, A. Ortiz, J. Ramirez +3
Respiratory diseases kill million of people each year. Diagnosis of these pathologies is a manual, time-consuming process that has inter and intra-observer variability, delaying di…
Automated detection and segmentation of non-mass enhancing breast tumors with dynamic contrast-enhanced magnetic resonance imaging
Ignacio Alvarez Illan, Javier Ramirez, Juan M. Gorriz +6
Non-mass enhancing lesions (NME) constitute a diagnostic challenge in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the breast. Computer Aided Diagnosis (CAD) s…