275 related articles for article (PubMed ID: 29375356)
1. Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Cognitively Unimpaired Individuals Using Multi-feature Kernel Discriminant Dictionary Learning.
Li Q; Wu X; Xu L; Chen K; Yao L;
Front Comput Neurosci; 2017; 11():117. PubMed ID: 29375356
[TBL] [Abstract][Full Text] [Related]
2. Multi-modal discriminative dictionary learning for Alzheimer's disease and mild cognitive impairment.
Li Q; Wu X; Xu L; Chen K; Yao L; Li R
Comput Methods Programs Biomed; 2017 Oct; 150():1-8. PubMed ID: 28859825
[TBL] [Abstract][Full Text] [Related]
3. Multi-modality sparse representation-based classification for Alzheimer's disease and mild cognitive impairment.
Xu L; Wu X; Chen K; Yao L
Comput Methods Programs Biomed; 2015 Nov; 122(2):182-90. PubMed ID: 26298855
[TBL] [Abstract][Full Text] [Related]
4. Prediction and Classification of Alzheimer's Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging Biomarkers.
Gupta Y; Lama RK; Kwon GR;
Front Comput Neurosci; 2019; 13():72. PubMed ID: 31680923
[TBL] [Abstract][Full Text] [Related]
5. Classification and Graphical Analysis of Alzheimer's Disease and Its Prodromal Stage Using Multimodal Features From Structural, Diffusion, and Functional Neuroimaging Data and the APOE Genotype.
Gupta Y; Kim JI; Kim BC; Kwon GR
Front Aging Neurosci; 2020; 12():238. PubMed ID: 32848713
[TBL] [Abstract][Full Text] [Related]
6. A Classification Algorithm by Combination of Feature Decomposition and Kernel Discriminant Analysis (KDA) for Automatic MR Brain Image Classification and AD Diagnosis.
Elahifasaee F; Li F; Yang M
Comput Math Methods Med; 2019; 2019():1437123. PubMed ID: 32082407
[TBL] [Abstract][Full Text] [Related]
7. Vision transformers for the prediction of mild cognitive impairment to Alzheimer's disease progression using mid-sagittal sMRI.
Hoang GM; Kim UH; Kim JG
Front Aging Neurosci; 2023; 15():1102869. PubMed ID: 37122374
[TBL] [Abstract][Full Text] [Related]
8. Multimodal Classification of Mild Cognitive Impairment Based on Partial Least Squares.
Wang P; Chen K; Yao L; Hu B; Wu X; Zhang J; Ye Q; Guo X;
J Alzheimers Dis; 2016 Aug; 54(1):359-71. PubMed ID: 27567818
[TBL] [Abstract][Full Text] [Related]
9. Multimodal classification of Alzheimer's disease and mild cognitive impairment using custom MKSCDDL kernel over CNN with transparent decision-making for explainable diagnosis.
Adarsh V; Gangadharan GR; Fiore U; Zanetti P
Sci Rep; 2024 Jan; 14(1):1774. PubMed ID: 38245656
[TBL] [Abstract][Full Text] [Related]
10. An ensemble learning system for a 4-way classification of Alzheimer's disease and mild cognitive impairment.
Yao D; Calhoun VD; Fu Z; Du Y; Sui J
J Neurosci Methods; 2018 May; 302():75-81. PubMed ID: 29578038
[TBL] [Abstract][Full Text] [Related]
11. Radiomics: a novel feature extraction method for brain neuron degeneration disease using
Li Y; Jiang J; Lu J; Jiang J; Zhang H; Zuo C
Ther Adv Neurol Disord; 2019; 12():1756286419838682. PubMed ID: 30956687
[TBL] [Abstract][Full Text] [Related]
12. Multi-Kernel Learning with Dartel Improves Combined MRI-PET Classification of Alzheimer's Disease in AIBL Data: Group and Individual Analyses.
Youssofzadeh V; McGuinness B; Maguire LP; Wong-Lin K
Front Hum Neurosci; 2017; 11():380. PubMed ID: 28790908
[TBL] [Abstract][Full Text] [Related]
13. Discriminative multi-task feature selection for multi-modality classification of Alzheimer's disease.
Ye T; Zu C; Jie B; Shen D; Zhang D;
Brain Imaging Behav; 2016 Sep; 10(3):739-49. PubMed ID: 26311394
[TBL] [Abstract][Full Text] [Related]
14. Deep learning application for the classification of Alzheimer's disease using
Park SW; Yeo NY; Kim Y; Byeon G; Jang JW
Sci Rep; 2023 May; 13(1):8096. PubMed ID: 37208383
[TBL] [Abstract][Full Text] [Related]
15. Gaussian discriminative component analysis for early detection of Alzheimer's disease: A supervised dimensionality reduction algorithm.
Fang C; Li C; Forouzannezhad P; Cabrerizo M; Curiel RE; Loewenstein D; Duara R; Adjouadi M;
J Neurosci Methods; 2020 Oct; 344():108856. PubMed ID: 32663548
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Progressive Mild Cognitive Impairment by Multi-Modal Neuroimaging Biomarkers.
Xu L; Wu X; Li R; Chen K; Long Z; Zhang J; Guo X; Yao L;
J Alzheimers Dis; 2016; 51(4):1045-56. PubMed ID: 26923024
[TBL] [Abstract][Full Text] [Related]
17. Multimodal manifold-regularized transfer learning for MCI conversion prediction.
Cheng B; Liu M; Suk HI; Shen D; Zhang D;
Brain Imaging Behav; 2015 Dec; 9(4):913-26. PubMed ID: 25702248
[TBL] [Abstract][Full Text] [Related]
18. Deep-Learning Radiomics for Discrimination Conversion of Alzheimer's Disease in Patients With Mild Cognitive Impairment: A Study Based on
Zhou P; Zeng R; Yu L; Feng Y; Chen C; Li F; Liu Y; Huang Y; Huang Z;
Front Aging Neurosci; 2021; 13():764872. PubMed ID: 34764864
[No Abstract] [Full Text] [Related]
19. Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes.
Wang Y; Xu C; Park JH; Lee S; Stern Y; Yoo S; Kim JH; Kim HS; Cha J;
Neuroimage Clin; 2019; 23():101859. PubMed ID: 31150957
[TBL] [Abstract][Full Text] [Related]
20. Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.
Lu D; Popuri K; Ding GW; Balachandar R; Beg MF;
Med Image Anal; 2018 May; 46():26-34. PubMed ID: 29502031
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
