Cargando…
A new classification network for diagnosing Alzheimer's disease in class-imbalance MRI datasets
Automatic identification of Alzheimer's Disease (AD) through magnetic resonance imaging (MRI) data can effectively assist to doctors diagnose and treat Alzheimer's. Current methods improve the accuracy of AD recognition, but they are insufficient to address the challenge of small interclas...
Autores principales: | Chen, Ziyang, Wang, Zhuowei, Zhao, Meng, Zhao, Qin, Liang, Xuehu, Li, Jiajian, Song, Xiaoyu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453266/ https://www.ncbi.nlm.nih.gov/pubmed/36090283 http://dx.doi.org/10.3389/fnins.2022.807085 |
Ejemplares similares
-
Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset
por: Guo, Hao, et al.
Publicado: (2017) -
New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification
por: Gu, Xiaoqing, et al.
Publicado: (2014) -
Functional connectivity between white matter and gray matter based on fMRI for Alzheimer's disease classification
por: Zhao, Jie, et al.
Publicado: (2019) -
Machine Learning Classification Combining Multiple Features of A Hyper-Network of fMRI Data in Alzheimer's Disease
por: Guo, Hao, et al.
Publicado: (2017) -
Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification
por: Böhle, Moritz, et al.
Publicado: (2019)