Generative adversarial networks for imputing missing data for big data clinical research

Generative adversarial networks for imputing missing data for big data clinical research

Abstract Background Missing data is a pervasive problem in clinical research. Generative adversarial imputation nets (GAIN), a novel machine learning data imputation approach, has the potential to substitute missing data accurately and efficiently but has not yet been evaluated in empirical big clin...

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Bibliographic Details
Main Authors: Weinan Dong, Daniel Yee Tak Fong, Jin-sun Yoon, Eric Yuk Fai Wan, Laura Elizabeth Bedford, Eric Ho Man Tang, Cindy Lo Kuen Lam
Format: Article
Language:English
Published: BMC 2021-04-01
Series:BMC Medical Research Methodology
Subjects:
Generative adversarial network
Missing data imputation
Machine learning
Clinical research
Big data
Online Access:https://doi.org/10.1186/s12874-021-01272-3

Internet

https://doi.org/10.1186/s12874-021-01272-3

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