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Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?
S Mirkin, BC Albensi - Frontiers in Aging Neuroscience, 2023 - frontiersin.org
Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory,
thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD …
thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD …
A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer's disease
C Wang, H Tachimori, H Yamaguchi… - Translational …, 2024 - nature.com
Alzheimer's disease is one of the most important health-care challenges in the world. For
decades, numerous efforts have been made to develop therapeutics for Alzheimer's …
decades, numerous efforts have been made to develop therapeutics for Alzheimer's …
[HTML][HTML] A hierarchical attention-based multimodal fusion framework for predicting the progression of Alzheimer's disease
Early detection and treatment can slow the progression of Alzheimer's Disease (AD), one of
the most common neurodegenerative diseases. Recent studies have demonstrated the …
the most common neurodegenerative diseases. Recent studies have demonstrated the …
A comparative study of GNN and MLP based machine learning for the diagnosis of Alzheimer's Disease involving data synthesis
Alzheimer's Disease (AD) is a neurodegenerative disease that commonly occurs in older
people. It is characterized by both cognitive and functional impairment. However, as AD has …
people. It is characterized by both cognitive and functional impairment. However, as AD has …
Vision transformer approach for classification of Alzheimer's disease using 18F-Florbetaben brain images
Dementia is a degenerative disease that is increasingly prevalent in an aging society.
Alzheimer's disease (AD), the most common type of dementia, is best mitigated via early …
Alzheimer's disease (AD), the most common type of dementia, is best mitigated via early …
[HTML][HTML] Applications of deep learning for drug discovery systems with bigdata
Y Matsuzaka, R Yashiro - BioMedInformatics, 2022 - mdpi.com
The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …
of pharmaceutical research and development, is progressing. By using the ability to process …
Himal: Multimodal hi erarchical m ulti-task a uxiliary l earning framework for predicting alzheimer's disease progression
Objective We aimed to develop and validate a novel multimodal framework Hi erarchical M
ulti-task A uxiliary L earning (HiMAL) framework, for predicting cognitive composite functions …
ulti-task A uxiliary L earning (HiMAL) framework, for predicting cognitive composite functions …
Assisting schizophrenia diagnosis using clinical electroencephalography and interpretable graph neural networks: a real-world and cross-site study
Schizophrenia (SCZ) is a chronic and serious mental disorder with a high mortality rate. At
present, there is a lack of objective, cost-effective and widely disseminated diagnosis tools to …
present, there is a lack of objective, cost-effective and widely disseminated diagnosis tools to …
Automatic assessment of disproportionately enlarged subarachnoid-space hydrocephalus from 3D MRI using two deep learning models
Background Disproportionately enlarged subarachnoid-space hydrocephalus (DESH) is a
key feature for Hakim disease (idiopathic normal pressure hydrocephalus: iNPH), but …
key feature for Hakim disease (idiopathic normal pressure hydrocephalus: iNPH), but …
Effect and Potential Mechanism of Immunotherapy on Cognitive Deficits in Animal Models of Alzheimer's Disease: A Systematic Review and Meta-Analysis
Z Zhai, F Kong, Z Zhu, J Dai, J Cai, D **e… - The American Journal of …, 2024 - Elsevier
Objective Immunotherapy has been reported to ameliorate Alzheimer's disease (AD) in the
animal model; however, the immunologic approaches and mechanisms have not been …
animal model; however, the immunologic approaches and mechanisms have not been …