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The application of unsupervised deep learning in predictive models using electronic health records
BACKGROUND: The main goal of this study is to explore the use of features representing patient-level electronic health record (EHR) data, generated by the unsupervised deep learning algorithm autoencoder, in predictive modeling. Since autoencoder features are unsupervised, this paper focuses on thei...
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| 出版年: | BMC Med Res Methodol |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7043035/ https://ncbi.nlm.nih.gov/pubmed/32101147 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12874-020-00923-1 |
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