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Generative adversarial networks for imputing missing data for big data clinical research
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 clinical dat...
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| Publicado no: | BMC Med Res Methodol |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8059005/ https://ncbi.nlm.nih.gov/pubmed/33879090 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12874-021-01272-3 |
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