Emotion recognition in EEG signals using deep learning methods: A review

M Jafari, A Shoeibi, M Khodatars… - Computers in Biology …, 2023 - Elsevier
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Information …, 2023 - Elsevier
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

[HTML][HTML] Computational approaches to explainable artificial intelligence: advances in theory, applications and trends

JM Górriz, I Álvarez-Illán, A Álvarez-Marquina, JE Arco… - Information …, 2023 - Elsevier
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

P Moridian, N Ghassemi, M Jafari… - Frontiers in Molecular …, 2022 - frontiersin.org
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 …

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review

M Jafari, A Shoeibi, M Khodatars, N Ghassemi… - Computers in Biology …, 2023 - Elsevier
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …

Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy …

A Shoeibi, N Ghassemi, M Khodatars, P Moridian… - Cognitive …, 2023 - Springer
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 …

QLBP: Dynamic patterns-based feature extraction functions for automatic detection of mental health and cognitive conditions using EEG signals

G Tasci, MV Gun, T Keles, B Tasci, PD Barua… - Chaos, Solitons & …, 2023 - Elsevier
Background Severe psychiatric disorders, including depressive disorders, schizophrenia
spectrum disorders, and intellectual disability, have devastating impacts on vital life domains …

Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023

M Jafari, D Sadeghi, A Shoeibi, H Alinejad-Rokny… - Applied …, 2024 - Springer
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …

A deep cross-modal neural cognitive diagnosis framework for modeling student performance

L Song, M He, X Shang, C Yang, J Liu, M Yu… - Expert Systems with …, 2023 - Elsevier
In intelligent education systems, one fundamental task is to predict student performance on
new exercises and estimate the knowledge proficiency of students on knowledge concepts …

Construction of data-driven performance digital twin for a real-world gas turbine anomaly detection considering uncertainty

Y Ma, X Zhu, J Lu, P Yang, J Sun - Sensors, 2023 - mdpi.com
Anomaly detection and failure prediction of gas turbines is of great importance for ensuring
reliable operation. This work presents a novel approach for anomaly detection based on a …