Treatment effect prediction with adversarial deep learning using electronic health records

Treatment effect prediction with adversarial deep learning using electronic health records

Abstract Background Treatment effect prediction (TEP) plays an important role in disease management by ensuring that the expected clinical outcomes are obtained after performing specialized and sophisticated treatments on patients given their personalized clinical status. In recent years, the wide a...

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Bibliographic Details
Main Authors:	Jiebin Chu, Wei Dong, Jinliang Wang, Kunlun He, Zhengxing Huang
Format:	Article
Language:	English
Published:	BMC 2020-12-01
Series:	BMC Medical Informatics and Decision Making
Subjects:	Treatment effect prediction Deep learning Adversarial learning Electronic health records
Online Access:	https://doi.org/10.1186/s12911-020-01151-9

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