Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …
disorder among the elderly and is a leading cause of dementia. AD results in significant …
Structural biomarker‐based Alzheimer's disease detection via ensemble learning techniques
Alzheimer's disease (AD) is a degenerative neurological disorder with incurable
characteristics. To identify the substantial solution, we used a structural biomarker (structural …
characteristics. To identify the substantial solution, we used a structural biomarker (structural …
Exploring the relationship among Alzheimer's disease, aging and cognitive scores through neuroimaging-based approach
J Sun, JDJ Han, W Chen - Scientific Reports, 2024 - nature.com
Alzheimer's disease (AD) is a fatal neurodegenerative disorder, with the Mini-Mental State
Examination (MMSE) and Clinical Dementia Rating (CDR) serving significant roles in …
Examination (MMSE) and Clinical Dementia Rating (CDR) serving significant roles in …
BrainDAS: Structure-aware domain adaptation network for multi-site brain network analysis
In the medical field, datasets are mostly integrated across sites due to difficult data
acquisition and insufficient data at a single site. The domain shift problem caused by the …
acquisition and insufficient data at a single site. The domain shift problem caused by the …
Adaptive critical subgraph mining for cognitive impairment conversion prediction with T1-MRI-based brain network
Prediction conversion of early-stage dementia is challenging due to subtle cognitive and
structural brain changes. Traditional T1-weighted magnetic resonance imaging (T1-MRI) …
structural brain changes. Traditional T1-weighted magnetic resonance imaging (T1-MRI) …
Cross-domain contrastive graph neural network for lncRNA–protein interaction prediction
H Li, B Wu, M Sun, Z Zhu, K Chen, H Ge - Knowledge-Based Systems, 2024 - Elsevier
Identifying lncRNA–protein interactions (LPIs) is an important biomedical task, facilitating the
comprehension of the biological functions and mechanisms of lncRNAs. Many …
comprehension of the biological functions and mechanisms of lncRNAs. Many …
Multimodal MRI-based detection of amyloid status in Alzheimer's disease continuum
Abstract Amyloid-$\beta $(A $\beta $) plaques in conjunction with hyperphosphorylated tau
proteins in the form of neurofibrillary tangles are the two neuropathological hallmarks of …
proteins in the form of neurofibrillary tangles are the two neuropathological hallmarks of …
Identifying ADHD‐Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network
Y Hu, J Ran, R Qiao, J Xu, C Tan, L Hu… - Neural Plasticity, 2024 - Wiley Online Library
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder
that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms …
that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms …
Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer's disease continuum
Amyloid-β (A β) plaques in conjunction with hyperphosphorylated tau proteins in the form of
neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer's disease. It is …
neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer's disease. It is …
An efficient vision transformer for Alzheimer's disease classification using magnetic resonance images
Alzheimer's disease (AD) is the most common dementia that is often seen among the
elderly. AD can cause the loss of cognitive ability and memory, which can result in death as …
elderly. AD can cause the loss of cognitive ability and memory, which can result in death as …