117 related articles for article (PubMed ID: 36277022)
41. Manifold regularized multitask feature learning for multimodality disease classification.
Jie B; Zhang D; Cheng B; Shen D;
Hum Brain Mapp; 2015 Feb; 36(2):489-507. PubMed ID: 25277605
[TBL] [Abstract][Full Text] [Related]
42. Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.
Choi H; Kim YK; Yoon EJ; Lee JY; Lee DS;
Eur J Nucl Med Mol Imaging; 2020 Feb; 47(2):403-412. PubMed ID: 31768599
[TBL] [Abstract][Full Text] [Related]
43. An Improved Deep Residual Network Prediction Model for the Early Diagnosis of Alzheimer's Disease.
Sun H; Wang A; Wang W; Liu C
Sensors (Basel); 2021 Jun; 21(12):. PubMed ID: 34207145
[TBL] [Abstract][Full Text] [Related]
44. 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]
45. 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]
46. 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]
47. FDG-PET for Prediction of AD Dementia in Mild Cognitive Impairment. A Review of the State of the Art with Particular Emphasis on the Comparison with Other Neuroimaging Modalities (MRI and Perfusion SPECT).
Sanchez-Catasus CA; Stormezand GN; van Laar PJ; De Deyn PP; Sanchez MA; Dierckx RA
Curr Alzheimer Res; 2017; 14(2):127-142. PubMed ID: 27357645
[TBL] [Abstract][Full Text] [Related]
48. Multimodal Discrimination of Alzheimer's Disease Based on Regional Cortical Atrophy and Hypometabolism.
Yun HJ; Kwak K; Lee JM;
PLoS One; 2015; 10(6):e0129250. PubMed ID: 26061669
[TBL] [Abstract][Full Text] [Related]
49. 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]
50. Anosognosia Is an Independent Predictor of Conversion From Mild Cognitive Impairment to Alzheimer's Disease and Is Associated With Reduced Brain Metabolism.
Gerretsen P; Chung JK; Shah P; Plitman E; Iwata Y; Caravaggio F; Nakajima S; Pollock BG; Graff-Guerrero A;
J Clin Psychiatry; 2017; 78(9):e1187-e1196. PubMed ID: 29022655
[TBL] [Abstract][Full Text] [Related]
51. 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]
52. 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]
53. Combination of 18F-FDG PET and cerebrospinal fluid biomarkers as a better predictor of the progression to Alzheimer's disease in mild cognitive impairment patients.
Choo IH; Ni R; Schöll M; Wall A; Almkvist O; Nordberg A
J Alzheimers Dis; 2013; 33(4):929-39. PubMed ID: 23047371
[TBL] [Abstract][Full Text] [Related]
54. Metabolic correlates of reserve and resilience in MCI due to Alzheimer's Disease (AD).
Bauckneht M; Chincarini A; Piva R; Arnaldi D; Girtler N; Massa F; Pardini M; Grazzini M; Efeturk H; Pagani M; Sambuceti G; Nobili F; Morbelli S
Alzheimers Res Ther; 2018 Apr; 10(1):35. PubMed ID: 29615111
[TBL] [Abstract][Full Text] [Related]
55. 18F-FDG PET diagnostic and prognostic patterns do not overlap in Alzheimer's disease (AD) patients at the mild cognitive impairment (MCI) stage.
Morbelli S; Bauckneht M; Arnaldi D; Picco A; Pardini M; Brugnolo A; Buschiazzo A; Pagani M; Girtler N; Nieri A; Chincarini A; De Carli F; Sambuceti G; Nobili F
Eur J Nucl Med Mol Imaging; 2017 Nov; 44(12):2073-2083. PubMed ID: 28785843
[TBL] [Abstract][Full Text] [Related]
56. 18F-Flortaucipir PET Associations with Cerebrospinal Fluid, Cognition, and Neuroimaging in Mild Cognitive Impairment due to Alzheimer's Disease.
Okafor M; Nye JA; Shokouhi M; Shaw LM; Goldstein F; Hajjar I
J Alzheimers Dis; 2020; 74(2):589-601. PubMed ID: 32065800
[TBL] [Abstract][Full Text] [Related]
57. Amyloid load but not regional glucose metabolism predicts conversion to Alzheimer's dementia in a memory clinic population.
Frings L; Hellwig S; Bormann T; Spehl TS; Buchert R; Meyer PT
Eur J Nucl Med Mol Imaging; 2018 Jul; 45(8):1442-1448. PubMed ID: 29546632
[TBL] [Abstract][Full Text] [Related]
58. Alzheimer's disease diagnosis framework from incomplete multimodal data using convolutional neural networks.
Abdelaziz M; Wang T; Elazab A
J Biomed Inform; 2021 Sep; 121():103863. PubMed ID: 34229061
[TBL] [Abstract][Full Text] [Related]
59. Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.
Liu M; Cheng D; Wang K; Wang Y;
Neuroinformatics; 2018 Oct; 16(3-4):295-308. PubMed ID: 29572601
[TBL] [Abstract][Full Text] [Related]
60. The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment - Beyond classical regression.
Teipel SJ; Kurth J; Krause B; Grothe MJ;
Neuroimage Clin; 2015; 8():583-93. PubMed ID: 26199870
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]