Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era-Reference-Cited by-同舟云学术

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Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era

Published:2023 Issue: Volume:16 Page:53-69
ISSN:1937-3333
Container-title:IEEE Reviews in Biomedical Engineering
language:
Short-container-title:IEEE Rev. Biomed. Eng.

Author:

Isgut Monica¹^ORCID,Gloster Logan¹,Choi Katherine²,Venugopalan Janani³,Wang May D.³^ORCID

Affiliation:

1. Department of Bioinformatics, School of Biology, Georgia Institute of Technology, Atlanta, GA, USA

2. School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA

3. Wallace H. Coulter School of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, USA

Funder

Georgia Tech Bioinformatics

COVID-19 Disruption Graduate Research Awards

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/4664312/10007429/09926151.pdf?arnumber=9926151

Reference169 articles.

1. MIDA: Multiple Imputation Using Denoising Autoencoders

2. MisGAN: Learning from incomplete data with generative adversarial networks;cheng-xian li,0

3. MIDIA: exploring denoising autoencoders for missing data imputation

4. Handling incomplete heterogeneous data using VAEs

5. imputeTS: Time Series Missing Value Imputation in R

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