Multi-Task Learning for Alzheimer's Disease Diagnosis and Mini-Mental State Examination Score Prediction
Accurately diagnosing Alzheimer's disease is essential for improving elderly health.
Meanwhile, accurate prediction of the mini-mental state examination score also can …
Meanwhile, accurate prediction of the mini-mental state examination score also can …
Mmgk: Multimodality multiview graph representations and knowledge embedding for mild cognitive impairment diagnosis
The diagnosis of mild cognitive impairment (MCI), which is an early stage of Alzheimer's
disease (AD), has great clinical significance. Medical imaging and gene sequencing …
disease (AD), has great clinical significance. Medical imaging and gene sequencing …
Automated Collateral Scoring on CT Angiography of Patients with Acute Ischemic Stroke Using Hybrid CNN and Transformer Network
Collateral scoring plays an important role in diagnosis and treatment decisions of acute
ischemic stroke (AIS). Most existing automated methods rely on vessel prominence and …
ischemic stroke (AIS). Most existing automated methods rely on vessel prominence and …
Research on magnetic resonance imaging in diagnosis of Alzheimer's disease
G Zhao, H Zhang, Y Xu, X Chu - European Journal of Medical Research, 2024 - Springer
As a common disease in the elderly, the diagnosis of Alzheimer's disease (AD) is of great
significance to the treatment and prognosis of the patients. Studies have found that magnetic …
significance to the treatment and prognosis of the patients. Studies have found that magnetic …
Deep learning methods for early detection of Alzheimer's disease using structural MR images: A survey
In this paper, we present an extensive review of the most recent works on Alzheimer's
disease (AD) prediction, focusing on Moderate Cognitive Impairment (MCI) conversion …
disease (AD) prediction, focusing on Moderate Cognitive Impairment (MCI) conversion …
Graph-based fusion of imaging, genetic and clinical data for degenerative disease diagnosis
Graph learning methods have achieved noteworthy performance in disease diagnosis due
to their ability to represent unstructured information such as inter-subject relationships. While …
to their ability to represent unstructured information such as inter-subject relationships. While …
RBS-Net: Hippocampus segmentation using multi-layer feature learning with the region, boundary and structure loss
Hippocampus has great influence over the Alzheimer's disease (AD) research because of its
essential role as a biomarker in the human brain. Thus the performance of hippocampus …
essential role as a biomarker in the human brain. Thus the performance of hippocampus …
Fusion of brain imaging genetic data for alzheimer's disease diagnosis and causal factors identification using multi-stream attention mechanisms and graph …
Correctly diagnosing Alzheimer's disease (AD) and identifying pathogenic brain regions and
genes play a vital role in understanding the AD and developing effective prevention and …
genes play a vital role in understanding the AD and developing effective prevention and …
[PDF][PDF] Hippocampus Segmentation using Patch-based Representation and ROC Label Enhancement
AD Tobar, JC Aguirre, DA Cardenas-Pena… - Engineering …, 2023 - engineeringletters.com
Brain Magnetic Resonance Imaging (MRI) is a quantitative neuroimaging technique to
support anatomical structure segmentation. Still, proper segmentation requires modeling …
support anatomical structure segmentation. Still, proper segmentation requires modeling …
Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder
Q Jia, X Wang, R Zhou, B Ma, F Fei… - Frontiers in …, 2023 - frontiersin.org
Background Artificial intelligence (AI) has been the subject of studies in autism spectrum
disorder (ASD) and may affect its identification, diagnosis, intervention, and other medical …
disorder (ASD) and may affect its identification, diagnosis, intervention, and other medical …