239 related articles for article (PubMed ID: 34421570)
1. Predicting MCI to AD Conversation Using Integrated sMRI and rs-fMRI: Machine Learning and Graph Theory Approach.
Zhang T; Liao Q; Zhang D; Zhang C; Yan J; Ngetich R; Zhang J; Jin Z; Li L
Front Aging Neurosci; 2021; 13():688926. PubMed ID: 34421570
[TBL] [Abstract][Full Text] [Related]
2. Alzheimer's Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield and Amygdala Volume of Structural MRI.
Khatri U; Kwon GR
Front Aging Neurosci; 2022; 14():818871. PubMed ID: 35707703
[TBL] [Abstract][Full Text] [Related]
3. Classification and Graphical Analysis of Alzheimer's Disease and Its Prodromal Stage Using Multimodal Features From Structural, Diffusion, and Functional Neuroimaging Data and the APOE Genotype.
Gupta Y; Kim JI; Kim BC; Kwon GR
Front Aging Neurosci; 2020; 12():238. PubMed ID: 32848713
[TBL] [Abstract][Full Text] [Related]
4. Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using MRI and Structural Network Features.
Wei R; Li C; Fogelson N; Li L
Front Aging Neurosci; 2016; 8():76. PubMed ID: 27148045
[TBL] [Abstract][Full Text] [Related]
5. Early Detection of Alzheimer's Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning.
Pan D; Zeng A; Jia L; Huang Y; Frizzell T; Song X
Front Neurosci; 2020; 14():259. PubMed ID: 32477040
[TBL] [Abstract][Full Text] [Related]
6. Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.
Hojjati SH; Ebrahimzadeh A; Khazaee A; Babajani-Feremi A;
J Neurosci Methods; 2017 Apr; 282():69-80. PubMed ID: 28286064
[TBL] [Abstract][Full Text] [Related]
7. An Efficient Combination among sMRI, CSF, Cognitive Score, and
Khatri U; Kwon GR
Comput Intell Neurosci; 2020; 2020():8015156. PubMed ID: 32565773
[TBL] [Abstract][Full Text] [Related]
8. Predicting conversion from MCI to AD by integrating rs-fMRI and structural MRI.
Hojjati SH; Ebrahimzadeh A; Khazaee A; Babajani-Feremi A;
Comput Biol Med; 2018 Nov; 102():30-39. PubMed ID: 30245275
[TBL] [Abstract][Full Text] [Related]
9. Identification of the Early Stage of Alzheimer's Disease Using Structural MRI and Resting-State fMRI.
Hojjati SH; Ebrahimzadeh A; Babajani-Feremi A
Front Neurol; 2019; 10():904. PubMed ID: 31543860
[TBL] [Abstract][Full Text] [Related]
10. Identifying Alzheimer's disease and mild cognitive impairment with atlas-based multi-modal metrics.
Long Z; Li J; Fan J; Li B; Du Y; Qiu S; Miao J; Chen J; Yin J; Jing B
Front Aging Neurosci; 2023; 15():1212275. PubMed ID: 37719872
[TBL] [Abstract][Full Text] [Related]
11. Prediction and Classification of Alzheimer's Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging Biomarkers.
Gupta Y; Lama RK; Kwon GR;
Front Comput Neurosci; 2019; 13():72. PubMed ID: 31680923
[TBL] [Abstract][Full Text] [Related]
12. Automatic classification of patients with Alzheimer's disease from structural MRI: a comparison of ten methods using the ADNI database.
Cuingnet R; Gerardin E; Tessieras J; Auzias G; Lehéricy S; Habert MO; Chupin M; Benali H; Colliot O;
Neuroimage; 2011 May; 56(2):766-81. PubMed ID: 20542124
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Multivariate Data Analysis and Machine Learning for Prediction of MCI-to-AD Conversion.
Skolariki K; Terrera GM; Danso S
Adv Exp Med Biol; 2020; 1194():81-103. PubMed ID: 32468526
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease.
Nanni L; Interlenghi M; Brahnam S; Salvatore C; Papa S; Nemni R; Castiglioni I;
Front Neurol; 2020; 11():576194. PubMed ID: 33250847
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Classification of Early and Late Mild Cognitive Impairment Using Functional Brain Network of Resting-State fMRI.
Zhang T; Zhao Z; Zhang C; Zhang J; Jin Z; Li L
Front Psychiatry; 2019; 10():572. PubMed ID: 31555157
[TBL] [Abstract][Full Text] [Related]
19. Classification of patients with MCI and AD from healthy controls using directed graph measures of resting-state fMRI.
Khazaee A; Ebrahimzadeh A; Babajani-Feremi A;
Behav Brain Res; 2017 Mar; 322(Pt B):339-350. PubMed ID: 27345822
[TBL] [Abstract][Full Text] [Related]
20. Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach.
Salvatore C; Cerasa A; Battista P; Gilardi MC; Quattrone A; Castiglioni I;
Front Neurosci; 2015; 9():307. PubMed ID: 26388719
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
