119 related articles for article (PubMed ID: 34460337)
1. A Bayesian group lasso classification for ADNI volumetrics data.
Majumder A; Maiti T; Datta S
Stat Methods Med Res; 2021 Oct; 30(10):2207-2220. PubMed ID: 34460337
[TBL] [Abstract][Full Text] [Related]
2. Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.
Dimitriadis SI; Liparas D; Tsolaki MN;
J Neurosci Methods; 2018 May; 302():14-23. PubMed ID: 29269320
[TBL] [Abstract][Full Text] [Related]
3. Generalized fused group lasso regularized multi-task feature learning for predicting cognitive outcomes in Alzheimers disease.
Cao P; Liu X; Liu H; Yang J; Zhao D; Huang M; Zaiane O
Comput Methods Programs Biomed; 2018 Aug; 162():19-45. PubMed ID: 29903486
[TBL] [Abstract][Full Text] [Related]
4. Tetrahedral spectral feature-Based bayesian manifold learning for grey matter morphometry: Findings from the Alzheimer's disease neuroimaging initiative.
Fan Y; Wang G; Dong Q; Liu Y; Leporé N; Wang Y
Med Image Anal; 2021 Aug; 72():102123. PubMed ID: 34214958
[TBL] [Abstract][Full Text] [Related]
5. Deep Learning for Alzheimer's Disease Classification using Texture Features.
So JH; Madusanka N; Choi HK; Choi BK; Park HG
Curr Med Imaging Rev; 2019; 15(7):689-698. PubMed ID: 32008517
[TBL] [Abstract][Full Text] [Related]
6. A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.
Spasov S; Passamonti L; Duggento A; Liò P; Toschi N;
Neuroimage; 2019 Apr; 189():276-287. PubMed ID: 30654174
[TBL] [Abstract][Full Text] [Related]
7. Effect of Education on Alzheimer's Disease-Related Neuroimaging Biomarkers in Healthy Controls, and Participants with Mild Cognitive Impairment and Alzheimer's Disease: A Cross-Sectional Study.
Wada M; Noda Y; Shinagawa S; Chung JK; Sawada K; Ogyu K; Tarumi R; Tsugawa S; Miyazaki T; Yamagata B; Graff-Guerrero A; Mimura M; Nakajima S;
J Alzheimers Dis; 2018; 63(2):861-869. PubMed ID: 29689728
[TBL] [Abstract][Full Text] [Related]
8. A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.
Liu M; Li F; Yan H; Wang K; Ma Y; ; Shen L; Xu M
Neuroimage; 2020 Mar; 208():116459. PubMed ID: 31837471
[TBL] [Abstract][Full Text] [Related]
9. Fused Group Lasso Regularized Multi-Task Feature Learning and Its Application to the Cognitive Performance Prediction of Alzheimer's Disease.
Liu X; Cao P; Wang J; Kong J; Zhao D
Neuroinformatics; 2019 Apr; 17(2):271-294. PubMed ID: 30284672
[TBL] [Abstract][Full Text] [Related]
10. Discriminative Sparse Features for Alzheimer's Disease Diagnosis Using Multimodal Image Data.
Ortiz A; Lozano F; Gorriz JM; Ramirez J; Martinez Murcia FJ;
Curr Alzheimer Res; 2018; 15(1):67-79. PubMed ID: 28934923
[TBL] [Abstract][Full Text] [Related]
11. Structured Sparse Kernel Learning for Imaging Genetics Based Alzheimer's Disease Diagnosis.
Peng J; An L; Zhu X; Jin Y; Shen D
Med Image Comput Comput Assist Interv; 2016 Oct; 9901():70-78. PubMed ID: 28580458
[TBL] [Abstract][Full Text] [Related]
12. Variational Bayesian partially linear mean shift models for high-dimensional Alzheimer's disease neuroimaging data.
Wu Y; Tang N
Stat Med; 2021 Jul; 40(15):3604-3624. PubMed ID: 33851463
[TBL] [Abstract][Full Text] [Related]
13. Predicting individual brain functional connectivity using a Bayesian hierarchical model.
Dai T; Guo Y;
Neuroimage; 2017 Feb; 147():772-787. PubMed ID: 27915121
[TBL] [Abstract][Full Text] [Related]
14. Evaluating the performance of Bayesian and frequentist approaches for longitudinal modeling: application to Alzheimer's disease.
Pérez-Millan A; Contador J; Tudela R; Niñerola-Baizán A; Setoain X; Lladó A; Sánchez-Valle R; Sala-Llonch R
Sci Rep; 2022 Aug; 12(1):14448. PubMed ID: 36002550
[TBL] [Abstract][Full Text] [Related]
15. Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study.
Kruggel F; Masaki F; Solodkin A;
J Neurosci Methods; 2017 Feb; 278():101-115. PubMed ID: 28057473
[TBL] [Abstract][Full Text] [Related]
16. Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease.
Yu G; Liu Y; Shen D
Brain Struct Funct; 2016 Sep; 221(7):3787-801. PubMed ID: 26476928
[TBL] [Abstract][Full Text] [Related]
17. The spike-and-slab elastic net as a classification tool in Alzheimer's disease.
Leach JM; Edwards LJ; Kana R; Visscher K; Yi N; Aban I;
PLoS One; 2022; 17(2):e0262367. PubMed ID: 35113902
[TBL] [Abstract][Full Text] [Related]
18. Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature ranking and a genetic algorithm.
Beheshti I; Demirel H; Matsuda H;
Comput Biol Med; 2017 Apr; 83():109-119. PubMed ID: 28260614
[TBL] [Abstract][Full Text] [Related]
19. Shape-Attributes of Brain Structures as Biomarkers for Alzheimer's Disease.
Glozman T; Solomon J; Pestilli F; Guibas L;
J Alzheimers Dis; 2017; 56(1):287-295. PubMed ID: 27911322
[TBL] [Abstract][Full Text] [Related]
20. Group Guided Fused Laplacian Sparse Group Lasso for Modeling Alzheimer's Disease Progression.
Liu X; Wang J; Ren F; Kong J
Comput Math Methods Med; 2020; 2020():4036560. PubMed ID: 32104201
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]