[HTML][HTML] Deep learning techniques for automated Alzheimer's and mild cognitive impairment disease using EEG signals: A comprehensive review of the last decade …

M Acharya, RC Deo, X Tao, PD Barua, A Devi… - Computer Methods and …, 2024 - Elsevier
Abstract Background and Objectives Mild Cognitive Impairment (MCI) and Alzheimer's
Disease (AD) are progressive neurological disorders that significantly impair the cognitive …

[HTML][HTML] Decoding covert visual attention to motion direction using graph theory features of EEG signals and quadratic discriminant analysis

Z Rezaei, MM Mohammadi, MR Daliri - Computers in Human Behavior …, 2024 - Elsevier
Visual attention is a type of selective attention that plays an important role in prioritizing and
processing the information received from the visual scenes around us. The brain is an …

Automatic Detection of Acute Leukemia (ALL and AML) Utilizing Customized Deep Graph Convolutional Neural Networks

L Zare, M Rahmani, N Khaleghi, S Sheykhivand… - Bioengineering, 2024 - mdpi.com
Leukemia is a malignant disease that impacts explicitly the blood cells, leading to life-
threatening infections and premature mortality. State-of-the-art machine-enabled …

Exploring Brain Activity in Different Mental Cognitive Workloads

SO Balani, AF Al-Hussainy… - Iranian Journal of …, 2024 - publish.kne-publishing.com
Objective: Understanding neural mechanisms underlying cognitive workload is crucial for
advancing our knowledge of human cognition and mental processes. In this study, we …

A new fuzzy-based ensemble framework based on attention-based deep learning architectures for automated detection of abnormal EEG

Z Yang, S Li - International Journal of System Assurance Engineering …, 2024 - Springer
Biomedical science research encompasses a wide array of fields such as biomedical
engineering, gene analysis, biomedical signal and image processing. The significance of …

Lightweight Graph Triplet Capsule Networks (LG-TriCapsNet) with Nearest Neighbour Graph (NNG) for Multi-Disease Neurological Classification

S Jain, R Srivastava - papers.ssrn.com
EEG signal classification of neurological disorders is a crucial task in the healthcare field
that requires accuracy and efficiency. It is a complex task to diagnose neurological diseases …