Progress of Mining Electronic Health Records based on Unsupervised Deep Learning Methods

Corresponding author: Li Jiao, li.jiao@imicams.ac.cn

DOI: 10.12201/bmr.202104.00013

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  Abstract: This study investigated the Autoencoder, Generative Adversarial Network, BERT and other unsupervised deep learning methods which were applied in electronic health record (EHR) data mining. Unsupervised deep learning technology improved the efficiency of medical knowledge discovery and clinical decision support, and promoted the development of personalized medicine.

  Key words: Unsupervised learning; Deep learning; Electronic health records; Data mining

  Submit time: 24 May 2021

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2021-04-16	bmr.202104.00013V1	Download

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