Cargando…
Identifying the regional substrates predictive of Alzheimer's disease progression through a convolutional neural network model and occlusion
Progressive brain atrophy is a key neuropathological hallmark of Alzheimer's disease (AD) dementia. However, atrophy patterns along the progression of AD dementia are diffuse and variable and are often missed by univariate methods. Consequently, identifying the major regional atrophy patterns u...
Autores principales: | Kwak, Kichang, Stanford, William, Dayan, Eran |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9704798/ https://www.ncbi.nlm.nih.gov/pubmed/35904092 http://dx.doi.org/10.1002/hbm.26026 |
Ejemplares similares
-
Model-based stratification of progression along the Alzheimer disease continuum highlights the centrality of biomarker synergies
por: Sadiq, Muhammad Usman, et al.
Publicado: (2022) -
Transfer learning‐trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression
por: Li, Yi, et al.
Publicado: (2021) -
Hypermixed Convolutional Neural Network for Retinal Vein Occlusion Classification
por: Zhang, Guanghua, et al.
Publicado: (2022) -
Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns
por: Kwak, Kichang, et al.
Publicado: (2021) -
Multimodal Discrimination of Alzheimer’s Disease Based on Regional Cortical Atrophy and Hypometabolism
por: Yun, Hyuk Jin, et al.
Publicado: (2015)