495 related articles for article (PubMed ID: 28666881)
1. Distinguishing early and late brain aging from the Alzheimer's disease spectrum: consistent morphological patterns across independent samples.
Doan NT; Engvig A; Zaske K; Persson K; Lund MJ; Kaufmann T; Cordova-Palomera A; Alnæs D; Moberget T; Brækhus A; Barca ML; Nordvik JE; Engedal K; Agartz I; Selbæk G; Andreassen OA; Westlye LT;
Neuroimage; 2017 Sep; 158():282-295. PubMed ID: 28666881
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease.
Tong T; Gao Q; Guerrero R; Ledig C; Chen L; Rueckert D; Initiative ADN
IEEE Trans Biomed Eng; 2017 Jan; 64(1):155-165. PubMed ID: 27046891
[TBL] [Abstract][Full Text] [Related]
4. Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.
Moradi E; Pepe A; Gaser C; Huttunen H; Tohka J;
Neuroimage; 2015 Jan; 104():398-412. PubMed ID: 25312773
[TBL] [Abstract][Full Text] [Related]
5. Volumes of lateral temporal and parietal structures distinguish between healthy aging, mild cognitive impairment, and Alzheimer's disease.
Hänggi J; Streffer J; Jäncke L; Hock C
J Alzheimers Dis; 2011; 26(4):719-34. PubMed ID: 21709375
[TBL] [Abstract][Full Text] [Related]
6. Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on univariate and multivariate models.
Liao W; Long X; Jiang C; Diao Y; Liu X; Zheng H; Zhang L;
Acad Radiol; 2014 May; 21(5):597-604. PubMed ID: 24433704
[TBL] [Abstract][Full Text] [Related]
7. Analysis of structural brain MRI and multi-parameter classification for Alzheimer's disease.
Zhang Y; Liu S
Biomed Tech (Berl); 2018 Jul; 63(4):427-437. PubMed ID: 28622141
[TBL] [Abstract][Full Text] [Related]
8. Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer's disease.
Chincarini A; Bosco P; Calvini P; Gemme G; Esposito M; Olivieri C; Rei L; Squarcia S; Rodriguez G; Bellotti R; Cerello P; De Mitri I; Retico A; Nobili F;
Neuroimage; 2011 Sep; 58(2):469-80. PubMed ID: 21718788
[TBL] [Abstract][Full Text] [Related]
9. Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.
Ramírez J; Górriz JM; Ortiz A; Martínez-Murcia FJ; Segovia F; Salas-Gonzalez D; Castillo-Barnes D; Illán IA; Puntonet CG;
J Neurosci Methods; 2018 May; 302():47-57. PubMed ID: 29242123
[TBL] [Abstract][Full Text] [Related]
10. Defining multivariate normative rules for healthy aging using neuroimaging and machine learning: an application to Alzheimer's disease.
Andrade de Oliveira A; Carthery-Goulart MT; Oliveira Júnior PP; Carrettiero DC; Sato JR
J Alzheimers Dis; 2015; 43(1):201-12. PubMed ID: 25079801
[TBL] [Abstract][Full Text] [Related]
11. Novel Cortical Thickness Pattern for Accurate Detection of Alzheimer's Disease.
Zheng W; Yao Z; Hu B; Gao X; Cai H; Moore P
J Alzheimers Dis; 2015; 48(4):995-1008. PubMed ID: 26444768
[TBL] [Abstract][Full Text] [Related]
12. T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease.
Haris M; Yadav SK; Rizwan A; Singh A; Cai K; Kaura D; Wang E; Davatzikos C; Trojanowski JQ; Melhem ER; Marincola FM; Borthakur A
Neuroimage Clin; 2015; 7():598-604. PubMed ID: 25844314
[TBL] [Abstract][Full Text] [Related]
13. Discriminant analysis of longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network features.
Li Y; Wang Y; Wu G; Shi F; Zhou L; Lin W; Shen D;
Neurobiol Aging; 2012 Feb; 33(2):427.e15-30. PubMed ID: 21272960
[TBL] [Abstract][Full Text] [Related]
14. Effects of imaging modalities, brain atlases and feature selection on prediction of Alzheimer's disease.
Ota K; Oishi N; Ito K; Fukuyama H; ;
J Neurosci Methods; 2015 Dec; 256():168-83. PubMed ID: 26318777
[TBL] [Abstract][Full Text] [Related]
15. Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer's disease.
Khazaee A; Ebrahimzadeh A; Babajani-Feremi A
Brain Imaging Behav; 2016 Sep; 10(3):799-817. PubMed ID: 26363784
[TBL] [Abstract][Full Text] [Related]
16. Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.
Dyrba M; Barkhof F; Fellgiebel A; Filippi M; Hausner L; Hauenstein K; Kirste T; Teipel SJ;
J Neuroimaging; 2015; 25(5):738-47. PubMed ID: 25644739
[TBL] [Abstract][Full Text] [Related]
17. Automated atrophy assessment for Alzheimer's disease diagnosis from brain MRI images.
Shaikh TA; Ali R
Magn Reson Imaging; 2019 Oct; 62():167-173. PubMed ID: 31279772
[TBL] [Abstract][Full Text] [Related]
18. 3D maps from multiple MRI illustrate changing atrophy patterns as subjects progress from mild cognitive impairment to Alzheimer's disease.
Whitwell JL; Przybelski SA; Weigand SD; Knopman DS; Boeve BF; Petersen RC; Jack CR
Brain; 2007 Jul; 130(Pt 7):1777-86. PubMed ID: 17533169
[TBL] [Abstract][Full Text] [Related]
19. An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease.
Schmitter D; Roche A; Maréchal B; Ribes D; Abdulkadir A; Bach-Cuadra M; Daducci A; Granziera C; Klöppel S; Maeder P; Meuli R; Krueger G;
Neuroimage Clin; 2015; 7():7-17. PubMed ID: 25429357
[TBL] [Abstract][Full Text] [Related]
20. Improving Alzheimer's Disease Classification by Combining Multiple Measures.
Liu J; Wang J; Tang Z; Hu B; Wu FX; Pan Y
IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(5):1649-1659. PubMed ID: 28749356
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]