Treatment effect prediction with adversarial deep learning using electronic health records

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 adoption...

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Detalles Bibliográficos
Autores principales: Chu, Jiebin, Dong, Wei, Wang, Jinliang, He, Kunlun, Huang, Zhengxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735418/
https://www.ncbi.nlm.nih.gov/pubmed/33317502
http://dx.doi.org/10.1186/s12911-020-01151-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735418/
https://www.ncbi.nlm.nih.gov/pubmed/33317502
http://dx.doi.org/10.1186/s12911-020-01151-9

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