Conditional Generative Adversarial Networks for Individualized Treatment Effect Estimation and Treatment Selection

Conditional Generative Adversarial Networks for Individualized Treatment Effect Estimation and Treatment Selection

Treatment response is heterogeneous. However, the classical methods treat the treatment response as homogeneous and estimate the average treatment effects. The traditional methods are difficult to apply to precision oncology. Artificial intelligence (AI) is a powerful tool for precision oncology. It...

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Bibliographic Details
Main Authors: Qiyang Ge, Xuelin Huang, Shenying Fang, Shicheng Guo, Yuanyuan Liu, Wei Lin, Momiao Xiong
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-12-01
Series:Frontiers in Genetics
Subjects:
causal inference
generative adversarial networks
counterfactuals
treatment estimation
precision medicine
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.585804/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2020.585804/full

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