167 related articles for article (PubMed ID: 31316553)
1. MildInt: Deep Learning-Based Multimodal Longitudinal Data Integration Framework.
Lee G; Kang B; Nho K; Sohn KA; Kim D
Front Genet; 2019; 10():617. PubMed ID: 31316553
[TBL] [Abstract][Full Text] [Related]
2. A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.
Spasov S; Passamonti L; Duggento A; Liò P; Toschi N;
Neuroimage; 2019 Apr; 189():276-287. PubMed ID: 30654174
[TBL] [Abstract][Full Text] [Related]
3. A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets.
Bayoudh K; Knani R; Hamdaoui F; Mtibaa A
Vis Comput; 2022; 38(8):2939-2970. PubMed ID: 34131356
[TBL] [Abstract][Full Text] [Related]
4. Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression
Abrol A; Fu Z; Du Y; Calhoun VD
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():4409-4413. PubMed ID: 31946844
[TBL] [Abstract][Full Text] [Related]
5. Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning.
Zhang W; Braden BB; Miranda G; Shu K; Wang S; Liu H; Wang Y
Neuroinformatics; 2022 Apr; 20(2):301-316. PubMed ID: 33978926
[TBL] [Abstract][Full Text] [Related]
6. Multimodal Neuroimaging Feature Learning With Multimodal Stacked Deep Polynomial Networks for Diagnosis of Alzheimer's Disease.
Shi J; Zheng X; Li Y; Zhang Q; Ying S
IEEE J Biomed Health Inform; 2018 Jan; 22(1):173-183. PubMed ID: 28113353
[TBL] [Abstract][Full Text] [Related]
7. DeAF: A multimodal deep learning framework for disease prediction.
Li K; Chen C; Cao W; Wang H; Han S; Wang R; Ye Z; Wu Z; Wang W; Cai L; Ding D; Yuan Z
Comput Biol Med; 2023 Apr; 156():106715. PubMed ID: 36867898
[TBL] [Abstract][Full Text] [Related]
8. Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review.
Ebrahimighahnavieh MA; Luo S; Chiong R
Comput Methods Programs Biomed; 2020 Apr; 187():105242. PubMed ID: 31837630
[TBL] [Abstract][Full Text] [Related]
9. A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.
Pang S; Yu Z; Orgun MA
Comput Methods Programs Biomed; 2017 Mar; 140():283-293. PubMed ID: 28254085
[TBL] [Abstract][Full Text] [Related]
10. Pancancer survival prediction using a deep learning architecture with multimodal representation and integration.
Fan Z; Jiang Z; Liang H; Han C
Bioinform Adv; 2023; 3(1):vbad006. PubMed ID: 36845202
[TBL] [Abstract][Full Text] [Related]
11. Learning using privileged information improves neuroimaging-based CAD of Alzheimer's disease: a comparative study.
Li Y; Meng F; Shi J;
Med Biol Eng Comput; 2019 Jul; 57(7):1605-1616. PubMed ID: 31028606
[TBL] [Abstract][Full Text] [Related]
12. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.
Pan X; Shen HB
BMC Bioinformatics; 2017 Feb; 18(1):136. PubMed ID: 28245811
[TBL] [Abstract][Full Text] [Related]
13. Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach.
Xu M; Ouyang L; Han L; Sun K; Yu T; Li Q; Tian H; Safarnejad L; Zhang H; Gao Y; Bao FS; Chen Y; Robinson P; Ge Y; Zhu B; Liu J; Chen S
J Med Internet Res; 2021 Jan; 23(1):e25535. PubMed ID: 33404516
[TBL] [Abstract][Full Text] [Related]
14. Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis.
Zhou T; Thung KH; Zhu X; Shen D
Hum Brain Mapp; 2019 Feb; 40(3):1001-1016. PubMed ID: 30381863
[TBL] [Abstract][Full Text] [Related]
15. A Multimodal Feature Fusion-Based Deep Learning Method for Online Fault Diagnosis of Rotating Machinery.
Zhou F; Hu P; Yang S; Wen C
Sensors (Basel); 2018 Oct; 18(10):. PubMed ID: 30340412
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. RNN-based longitudinal analysis for diagnosis of Alzheimer's disease.
Cui R; Liu M;
Comput Med Imaging Graph; 2019 Apr; 73():1-10. PubMed ID: 30763637
[TBL] [Abstract][Full Text] [Related]
18. Learning-based Cancer Treatment Outcome Prognosis using Multimodal Biomarkers.
Saad M; He S; Thorstad W; Gay H; Barnett D; Zhao Y; Ruan S; Wang X; Li H
IEEE Trans Radiat Plasma Med Sci; 2022 Feb; 6(2):231-244. PubMed ID: 35520102
[TBL] [Abstract][Full Text] [Related]
19. Progressive Learning of a Multimodal Classifier Accounting for Different Modality Combinations.
John V; Kawanishi Y
Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430579
[TBL] [Abstract][Full Text] [Related]
20. Effective Diagnosis of Alzheimer's Disease
Bi XA; Cai R; Wang Y; Liu Y
Front Genet; 2019; 10():976. PubMed ID: 31649738
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]