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CURE: A Pre-training Framework on Large-scale Patient Data for Treatment Effect Estimation
2022-09-10
health informatics
Title + abstract only
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Treatment effect estimation (TEE) refers to the estimation of causal effects, and it aims to compare the difference among treatment strategies on important outcomes. Current machine learning based methods are mainly trained on labeled data with specific treatments or outcomes of interest, which can be sub-optimal if the labeled data are limited. In this paper, we propose a novel transformer-based pre-training and fine-tuning framework called CURE for TEE from observational data. CURE is pre-trai...
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