Generative Adversarial Networks Enhanced Pre-training for Insufficient Electronic Health Records Modeling-Reference-Cited by-同舟云学术

Generative Adversarial Networks Enhanced Pre-training for Insufficient Electronic Health Records Modeling

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Ren Houxing¹,Wang Jingyuan¹,Zhao Wayne Xin²

Affiliation:

1. Beihang University & Peng Cheng Laboratory, Beijing, China

2. Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China

Funder

The Fundamental Research Funds for the Central Universities

The National Key R&D Program of China

The National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539020

Reference40 articles.

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4. Zhengping Che , Yu Cheng , Shuangfei Zhai , Zhaonan Sun , and Yan Liu . 2017 . Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. In ICDM'17 . IEEE Computer Society, 787--792. Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, and Yan Liu. 2017. Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. In ICDM'17. IEEE Computer Society, 787--792.

5. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

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