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MISSING DATA IMPUTATION IN THE ELECTRONIC HEALTH RECORD USING DEEPLY LEARNED AUTOENCODERS()
Electronic health records (EHRs) have become a vital source of patient outcome data but the widespread prevalence of missing data presents a major challenge. Different causes of missing data in the EHR data may introduce unintentional bias. Here, we compare the effectiveness of popular multiple impu...
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| Pubblicato in: | Pac Symp Biocomput |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5144587/ https://ncbi.nlm.nih.gov/pubmed/27896976 |
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