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Items: 1 to 20 of 208

1.

Histogram-Based Features Selection and Volume of Interest Ranking for Brain PET Image Classification.

Garali I, Adel M, Bourennane S, Guedj E.

IEEE J Transl Eng Health Med. 2018 Mar 16;6:2100212. doi: 10.1109/JTEHM.2018.2796600. eCollection 2018.

2.

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images.

Lu D, Popuri K, Ding GW, Balachandar R, Beg MF; Alzheimer’s Disease Neuroimaging Initiative.

Sci Rep. 2018 Apr 9;8(1):5697. doi: 10.1038/s41598-018-22871-z.

3.

Sub-Network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis.

Jie B, Liu M, Zhang D, Shen D.

IEEE Trans Image Process. 2018 May;27(5):2340-2353. doi: 10.1109/TIP.2018.2799706.

PMID:
29470170
4.

Sparse Multi-view Task-Centralized Learning for ASD Diagnosis.

Wang J, Wang Q, Wang S, Shen D.

Mach Learn Med Imaging. 2017;10541:159-167. doi: 10.1007/978-3-319-67389-9_19. Epub 2017 Sep 7.

5.

Classification of MRI and psychological testing data based on support vector machine.

Yang W, Chen X, Cohen DS, Rosin ER, Toga AW, Thompson PM, Huang X.

Int J Clin Exp Med. 2017 Dec;10(12):16004-16026.

6.

Multimodal Discrimination between Normal Aging, Mild Cognitive Impairment and Alzheimer's Disease and Prediction of Cognitive Decline.

Bauer CM, Cabral HJ, Killiany RJ.

Diagnostics (Basel). 2018 Feb 6;8(1). pii: E14. doi: 10.3390/diagnostics8010014.

7.

Combining multi-modality data for searching biomarkers in schizophrenia.

Guo S, Huang CC, Zhao W, Yang AC, Lin CP, Nichols T, Tsai SJ.

PLoS One. 2018 Feb 1;13(2):e0191202. doi: 10.1371/journal.pone.0191202. eCollection 2018.

8.

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; Alzheimer's Disease Neuroimaging Initiative.

Front Comput Neurosci. 2018 Jan 9;11:117. doi: 10.3389/fncom.2017.00117. eCollection 2017.

9.

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease.

Liu X, Chen K, Wu T, Weidman D, Lure F, Li J.

Transl Res. 2018 Apr;194:56-67. doi: 10.1016/j.trsl.2018.01.001. Epub 2018 Jan 10. Review.

PMID:
29352978
10.

Embedding Anatomical or Functional Knowledge in Whole-Brain Multiple Kernel Learning Models.

Schrouff J, Monteiro JM, Portugal L, Rosa MJ, Phillips C, Mourão-Miranda J.

Neuroinformatics. 2018 Jan;16(1):117-143. doi: 10.1007/s12021-017-9347-8.

11.

Factors influencing accuracy of cortical thickness in the diagnosis of Alzheimer's disease.

Belathur Suresh M, Fischl B, Salat DH; Alzheimer's Disease Neuroimaging Initiative (ADNI).

Hum Brain Mapp. 2018 Apr;39(4):1500-1515. doi: 10.1002/hbm.23922. Epub 2017 Dec 21.

PMID:
29271096
12.

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.

13.

Characterizing biomarker features of cognitively normal individuals with ventriculomegaly.

Li X, Ba M, Ng KP, Mathotaarachchi S, Pascoal TA, Rosa-Neto P, Gauthier S.

Alzheimers Dement (Amst). 2017 Sep 5;10:12-21. doi: 10.1016/j.dadm.2017.08.001. eCollection 2018.

14.

Classifying MCI Subtypes in Community-Dwelling Elderly Using Cross-Sectional and Longitudinal MRI-Based Biomarkers.

Guan H, Liu T, Jiang J, Tao D, Zhang J, Niu H, Zhu W, Wang Y, Cheng J, Kochan NA, Brodaty H, Sachdev P, Wen W.

Front Aging Neurosci. 2017 Sep 26;9:309. doi: 10.3389/fnagi.2017.00309. eCollection 2017.

15.

The prevalence and biomarkers' characteristic of rapidly progressive Alzheimer's disease from the Alzheimer's Disease Neuroimaging Initiative database.

Ba M, Li X, Ng KP, Pascoal TA, Mathotaarachchi S, Rosa-Neto P, Gauthier S; Alzheimer's Disease Neuroimaging Initiative.

Alzheimers Dement (N Y). 2017 Feb 9;3(1):107-113. doi: 10.1016/j.trci.2016.12.005. eCollection 2017 Jan.

16.

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.

17.

Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer's dementia.

Frölich L, Peters O, Lewczuk P, Gruber O, Teipel SJ, Gertz HJ, Jahn H, Jessen F, Kurz A, Luckhaus C, Hüll M, Pantel J, Reischies FM, Schröder J, Wagner M, Rienhoff O, Wolf S, Bauer C, Schuchhardt J, Heuser I, Rüther E, Henn F, Maier W, Wiltfang J, Kornhuber J.

Alzheimers Res Ther. 2017 Oct 10;9(1):84. doi: 10.1186/s13195-017-0301-7.

18.

Monitoring disease progression in mild cognitive impairment: Associations between atrophy patterns, cognition, APOE and amyloid.

Falahati F, Ferreira D, Muehlboeck JS, Eriksdotter M, Simmons A, Wahlund LO, Westman E.

Neuroimage Clin. 2017 Aug 14;16:418-428. doi: 10.1016/j.nicl.2017.08.014. eCollection 2017.

19.

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features.

Singanamalli A, Wang H, Madabhushi A; Alzheimer’s Disease Neuroimaging Initiative.

Sci Rep. 2017 Aug 15;7(1):8137. doi: 10.1038/s41598-017-03925-0.

20.

Enhanced Data Representation by Kernel Metric Learning for Dementia Diagnosis.

Cárdenas-Peña D, Collazos-Huertas D, Castellanos-Dominguez G.

Front Neurosci. 2017 Jul 26;11:413. doi: 10.3389/fnins.2017.00413. eCollection 2017.

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