250 related articles for article (PubMed ID: 31102761)
1. Voxel-Based Morphometry: Improving the Diagnosis of Alzheimer's Disease Based on an Extreme Learning Machine Method from the ADNI cohort.
Zhang F; Tian S; Chen S; Ma Y; Li X; Guo X
Neuroscience; 2019 Aug; 414():273-279. PubMed ID: 31102761
[TBL] [Abstract][Full Text] [Related]
2. Early diagnosis of Alzheimer's disease using combined features from voxel-based morphometry and cortical, subcortical, and hippocampus regions of MRI T1 brain images.
Gupta Y; Lee KH; Choi KY; Lee JJ; Kim BC; Kwon GR; ;
PLoS One; 2019; 14(10):e0222446. PubMed ID: 31584953
[TBL] [Abstract][Full Text] [Related]
3. Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation.
Ikemitsu N; Kanazawa Y; Haga A; Hayashi H; Matsumoto Y; Harada M
Acta Radiol; 2024 Apr; 65(4):359-366. PubMed ID: 38196180
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes.
Wang Y; Xu C; Park JH; Lee S; Stern Y; Yoo S; Kim JH; Kim HS; Cha J;
Neuroimage Clin; 2019; 23():101859. PubMed ID: 31150957
[TBL] [Abstract][Full Text] [Related]
6. Independent Component Analysis-Support Vector Machine-Based Computer-Aided Diagnosis System for Alzheimer's with Visual Support.
Khedher L; Illán IA; Górriz JM; Ramírez J; Brahim A; Meyer-Baese A
Int J Neural Syst; 2017 May; 27(3):1650050. PubMed ID: 27776438
[TBL] [Abstract][Full Text] [Related]
7. Probability distribution function-based classification of structural MRI for the detection of Alzheimer's disease.
Beheshti I; Demirel H;
Comput Biol Med; 2015 Sep; 64():208-16. PubMed ID: 26226415
[TBL] [Abstract][Full Text] [Related]
8. 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. PubMed ID: 26742127
[TBL] [Abstract][Full Text] [Related]
9. Integrating spatial-anatomical regularization and structure sparsity into SVM: Improving interpretation of Alzheimer's disease classification.
Sun Z; Qiao Y; Lelieveldt BPF; Staring M;
Neuroimage; 2018 Sep; 178():445-460. PubMed ID: 29802968
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Contourlet-based hippocampal magnetic resonance imaging texture features for multivariant classification and prediction of Alzheimer's disease.
Gao N; Tao LX; Huang J; Zhang F; Li X; O'Sullivan F; Chen SP; Tian SJ; Mahara G; Luo YX; Gao Q; Liu XT; Wang W; Liang ZG; Guo XH
Metab Brain Dis; 2018 Dec; 33(6):1899-1909. PubMed ID: 30178281
[TBL] [Abstract][Full Text] [Related]
13. Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.
Kim J; Lee B
Hum Brain Mapp; 2018 Sep; 39(9):3728-3741. PubMed ID: 29736986
[TBL] [Abstract][Full Text] [Related]
14. Random support vector machine cluster analysis of resting-state fMRI in Alzheimer's disease.
Bi XA; Shu Q; Sun Q; Xu Q
PLoS One; 2018; 13(3):e0194479. PubMed ID: 29570705
[TBL] [Abstract][Full Text] [Related]
15. Alzheimer's Disease Computer-Aided Diagnosis: Histogram-Based Analysis of Regional MRI Volumes for Feature Selection and Classification.
Ruiz E; Ramírez J; Górriz JM; Casillas J;
J Alzheimers Dis; 2018; 65(3):819-842. PubMed ID: 29966190
[TBL] [Abstract][Full Text] [Related]
16. Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer's dementia diagnosis using multi-measure rs-fMRI spatial patterns.
Nguyen DT; Ryu S; Qureshi MNI; Choi M; Lee KH; Lee B
PLoS One; 2019; 14(2):e0212582. PubMed ID: 30794629
[TBL] [Abstract][Full Text] [Related]
17. Multimodal Classification of Mild Cognitive Impairment Based on Partial Least Squares.
Wang P; Chen K; Yao L; Hu B; Wu X; Zhang J; Ye Q; Guo X;
J Alzheimers Dis; 2016 Aug; 54(1):359-71. PubMed ID: 27567818
[TBL] [Abstract][Full Text] [Related]
18. Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.
Jongin Kim ; Boreom Lee
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():1990-1993. PubMed ID: 29060285
[TBL] [Abstract][Full Text] [Related]
19. A novel joint HCPMMP method for automatically classifying Alzheimer's and different stage MCI patients.
Sheng J; Wang B; Zhang Q; Liu Q; Ma Y; Liu W; Shao M; Chen B
Behav Brain Res; 2019 Jun; 365():210-221. PubMed ID: 30836158
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]