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Items: 1 to 20 of 71

1.

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases.

Rondina JM, Ferreira LK, de Souza Duran FL, Kubo R, Ono CR, Leite CC, Smid J, Nitrini R, Buchpiguel CA, Busatto GF.

Neuroimage Clin. 2017 Nov 9;17:628-641. doi: 10.1016/j.nicl.2017.10.026. eCollection 2018.

2.

Generative models for network neuroscience: prospects and promise.

Betzel RF, Bassett DS.

J R Soc Interface. 2017 Nov;14(136). pii: 20170623. doi: 10.1098/rsif.2017.0623. Epub 2017 Nov 29. Review.

3.

Diagnosis of Alzheimer's Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features.

Lama RK, Gwak J, Park JS, Lee SW.

J Healthc Eng. 2017;2017:5485080. doi: 10.1155/2017/5485080. Epub 2017 Jun 18.

4.

Hybrid High-order Functional Connectivity Networks Using Resting-state Functional MRI for Mild Cognitive Impairment Diagnosis.

Zhang Y, Zhang H, Chen X, Lee SW, Shen D.

Sci Rep. 2017 Jul 26;7(1):6530. doi: 10.1038/s41598-017-06509-0.

5.

Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry.

Tsao S, Gajawelli N, Zhou J, Shi J, Ye J, Wang Y, Leporé N.

Brain Behav. 2017 Jun 9;7(7):e00733. doi: 10.1002/brb3.733. eCollection 2017 Jul.

6.

Predicting two-year survival versus non-survival after first myocardial infarction using machine learning and Swedish national register data.

Wallert J, Tomasoni M, Madison G, Held C.

BMC Med Inform Decis Mak. 2017 Jul 5;17(1):99. doi: 10.1186/s12911-017-0500-y.

7.

Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images.

Zhang J, Liu M, Le An, Gao Y, Shen D.

IEEE J Biomed Health Inform. 2017 Nov;21(6):1607-1616. doi: 10.1109/JBHI.2017.2704614. Epub 2017 May 16.

8.

A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.

Rathore S, Habes M, Iftikhar MA, Shacklett A, Davatzikos C.

Neuroimage. 2017 Jul 15;155:530-548. doi: 10.1016/j.neuroimage.2017.03.057. Epub 2017 Apr 13. Review.

PMID:
28414186
9.

Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder.

Schnyer DM, Clasen PC, Gonzalez C, Beevers CG.

Psychiatry Res. 2017 Jun 30;264:1-9. doi: 10.1016/j.pscychresns.2017.03.003. Epub 2017 Mar 23.

PMID:
28388468
10.

Prediction and classification of Alzheimer disease based on quantification of MRI deformation.

Long X, Chen L, Jiang C, Zhang L; Alzheimer’s Disease Neuroimaging Initiative.

PLoS One. 2017 Mar 6;12(3):e0173372. doi: 10.1371/journal.pone.0173372. eCollection 2017.

11.

Classification of brain disease in magnetic resonance images using two-stage local feature fusion.

Li T, Li W, Yang Y, Zhang W.

PLoS One. 2017 Feb 16;12(2):e0171749. doi: 10.1371/journal.pone.0171749. eCollection 2017.

12.

Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease.

Moradi E, Hallikainen I, Hänninen T, Tohka J; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage Clin. 2016 Dec 18;13:415-427. doi: 10.1016/j.nicl.2016.12.011. eCollection 2017.

13.

Longitudinal measurement and hierarchical classification framework for the prediction of Alzheimer's disease.

Huang M, Yang W, Feng Q, Chen W; Alzheimer’s Disease Neuroimaging Initiative.

Sci Rep. 2017 Jan 12;7:39880. doi: 10.1038/srep39880.

14.

Shape-Attributes of Brain Structures as Biomarkers for Alzheimer's Disease.

Glozman T, Solomon J, Pestilli F, Guibas L; Alzheimer’s Disease Neuroimaging Initiative.

J Alzheimers Dis. 2017;56(1):287-295. doi: 10.3233/JAD-160900.

15.

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

Mete M, Sakoglu U, Spence JS, Devous MD Sr, Harris TS, Adinoff B.

BMC Bioinformatics. 2016 Oct 6;17(Suppl 13):357.

16.

Automated identification of dementia using medical imaging: a survey from a pattern classification perspective.

Zheng C, Xia Y, Pan Y, Chen J.

Brain Inform. 2016 Mar;3(1):17-27. Epub 2015 Dec 21.

17.

Dysregulation of Autophagy, Mitophagy, and Apoptotic Genes in the Medial Temporal Lobe Cortex in an Ischemic Model of Alzheimer's Disease.

Ułamek-Kozioł M, Kocki J, Bogucka-Kocka A, Petniak A, Gil-Kulik P, Januszewski S, Bogucki J, Jabłoński M, Furmaga-Jabłońska W, Brzozowska J, Czuczwar SJ, Pluta R.

J Alzheimers Dis. 2016 Jul 27;54(1):113-21. doi: 10.3233/JAD-160387.

18.

Prediction of brain maturity in infants using machine-learning algorithms.

Smyser CD, Dosenbach NU, Smyser TA, Snyder AZ, Rogers CE, Inder TE, Schlaggar BL, Neil JJ.

Neuroimage. 2016 Aug 1;136:1-9. doi: 10.1016/j.neuroimage.2016.05.029. Epub 2016 May 11.

19.

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

Arbabshirani MR, Plis S, Sui J, Calhoun VD.

Neuroimage. 2017 Jan 15;145(Pt B):137-165. doi: 10.1016/j.neuroimage.2016.02.079. Epub 2016 Mar 21.

PMID:
27012503
20.

Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment.

Liu M, Zhang D, Shen D.

IEEE Trans Med Imaging. 2016 Jun;35(6):1463-74. doi: 10.1109/TMI.2016.2515021. Epub 2016 Jan 5.

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