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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...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059005/ https://www.ncbi.nlm.nih.gov/pubmed/33879090 http://dx.doi.org/10.1186/s12874-021-01272-3 |