188 related articles for article (PubMed ID: 35169788)
1. Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems.
Dai Z; Bu Z; Long Q
Proc Int Conf Mach Learn Appl; 2021 Dec; 2021():791-798. PubMed ID: 35169788
[TBL] [Abstract][Full Text] [Related]
2. Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data.
Dai Z; Bu Z; Long Q
Proc Mach Learn Res; 2022 Dec; 189():265-279. PubMed ID: 37457613
[TBL] [Abstract][Full Text] [Related]
3. Detracking Autoencoding Conditional Generative Adversarial Network: Improved Generative Adversarial Network Method for Tabular Missing Value Imputation.
Liu J; Duan Z; Hu X; Zhong J; Yin Y
Entropy (Basel); 2024 May; 26(5):. PubMed ID: 38785651
[TBL] [Abstract][Full Text] [Related]
4. A joint learning method for incomplete and imbalanced data in electronic health record based on generative adversarial networks.
Weng X; Song H; Lin Y; Wu Y; Zhang X; Liu B; Yang J
Comput Biol Med; 2024 Jan; 168():107687. PubMed ID: 38007974
[TBL] [Abstract][Full Text] [Related]
5. Electronic medical records imputation by temporal Generative Adversarial Network.
Yin Y; Yuan Z; Tanvir IM; Bao X
BioData Min; 2024 Jun; 17(1):19. PubMed ID: 38926718
[TBL] [Abstract][Full Text] [Related]
6. PC-GAIN: Pseudo-label conditional generative adversarial imputation networks for incomplete data.
Wang Y; Li D; Li X; Yang M
Neural Netw; 2021 Sep; 141():395-403. PubMed ID: 34139636
[TBL] [Abstract][Full Text] [Related]
7. A novel missing data imputation approach based on clinical conditional Generative Adversarial Networks applied to EHR datasets.
Bernardini M; Doinychko A; Romeo L; Frontoni E; Amini MR
Comput Biol Med; 2023 Sep; 163():107188. PubMed ID: 37393785
[TBL] [Abstract][Full Text] [Related]
8. A Missing Traffic Data Imputation Method Based on a Diffusion Convolutional Neural Network-Generative Adversarial Network.
Zhang C; Zhou L; Xiao X; Xu D
Sensors (Basel); 2023 Dec; 23(23):. PubMed ID: 38067974
[TBL] [Abstract][Full Text] [Related]
9. DeepMicroGen: a generative adversarial network-based method for longitudinal microbiome data imputation.
Choi JM; Ji M; Watson LT; Zhang L
Bioinformatics; 2023 May; 39(5):. PubMed ID: 37099704
[TBL] [Abstract][Full Text] [Related]
10. Generative adversarial networks for imputing missing data for big data clinical research.
Dong W; Fong DYT; Yoon JS; Wan EYF; Bedford LE; Tang EHM; Lam CLK
BMC Med Res Methodol; 2021 Apr; 21(1):78. PubMed ID: 33879090
[TBL] [Abstract][Full Text] [Related]
11. scMultiGAN: cell-specific imputation for single-cell transcriptomes with multiple deep generative adversarial networks.
Wang T; Zhao H; Xu Y; Wang Y; Shang X; Peng J; Xiao B
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37903416
[TBL] [Abstract][Full Text] [Related]
12. MISNN: Multiple Imputation via Semi-parametric Neural Networks.
Bu Z; Dai Z; Zhang Y; Long Q
Adv Knowl Discov Data Min; 2023 May; 13935():430-442. PubMed ID: 38370342
[TBL] [Abstract][Full Text] [Related]
13. Recovering from missing data in population imaging - Cardiac MR image imputation via conditional generative adversarial nets.
Xia Y; Zhang L; Ravikumar N; Attar R; Piechnik SK; Neubauer S; Petersen SE; Frangi AF
Med Image Anal; 2021 Jan; 67():101812. PubMed ID: 33129140
[TBL] [Abstract][Full Text] [Related]
14. Missing Data Imputation Method Combining Random Forest and Generative Adversarial Imputation Network.
Ou H; Yao Y; He Y
Sensors (Basel); 2024 Feb; 24(4):. PubMed ID: 38400270
[TBL] [Abstract][Full Text] [Related]
15. ImputeGAN: Generative Adversarial Network for Multivariate Time Series Imputation.
Qin R; Wang Y
Entropy (Basel); 2023 Jan; 25(1):. PubMed ID: 36673278
[TBL] [Abstract][Full Text] [Related]
16. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network.
Huang Z; Wang J; Lu X; Mohd Zain A; Yu G
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36733262
[TBL] [Abstract][Full Text] [Related]
17. VIGAN: Missing View Imputation with Generative Adversarial Networks.
Shang C; Palmer A; Sun J; Chen KS; Lu J; Bi J
Proc IEEE Int Conf Big Data; 2017; 2017():766-775. PubMed ID: 29457155
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning Methods for Omics Data Imputation.
Huang L; Song M; Shen H; Hong H; Gong P; Deng HW; Zhang C
Biology (Basel); 2023 Oct; 12(10):. PubMed ID: 37887023
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of Multiple Imputation with Large Proportions of Missing Data: How Much Is Too Much?
Lee JH; Huber JC
Iran J Public Health; 2021 Jul; 50(7):1372-1380. PubMed ID: 34568175
[TBL] [Abstract][Full Text] [Related]
20. A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study.
De Silva AP; Moreno-Betancur M; De Livera AM; Lee KJ; Simpson JA
BMC Med Res Methodol; 2017 Jul; 17(1):114. PubMed ID: 28743256
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
