The application of unsupervised deep learning in predictive models using electronic health records
Abstract 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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-02-01
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| Series: | BMC Medical Research Methodology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12874-020-00923-1 |