Corpus ID: 88517061

Efficient and Robust Semi-Supervised Estimation of Average Treatment Effects in Electronic Medical Records Data

@article{Cheng2018EfficientAR,
  title={Efficient and Robust Semi-Supervised Estimation of Average Treatment Effects in Electronic Medical Records Data},
  author={David Cheng and Ashwin N. Ananthakrishnan and Tianxi Cai},
  journal={arXiv: Methodology},
  year={2018}
}
There is strong interest in conducting comparative effectiveness research (CER) in electronic medical records (EMR) to evaluate treatment strategies among real-world patients. Inferring causal effects in EMR data, however, is challenging due to the lack of direct observation on pre-specified gold-standard outcomes, in addition to the observational nature of the data. Extracting gold-standard outcomes often requires labor-intensive medical chart review, which is unfeasible for large studies… Expand

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