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The application of unsupervised deep learning in predictive models using electronic health records
28
Zitationen
5
Autoren
2020
Jahr
Abstract
We conclude that autoencoder can create useful features representing the entire space of EHR data and which are applicable to a wide array of predictive tasks. Together with important response-specific predictors, we can derive efficient and robust predictive models with less labor in data extraction and model training.
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