2022
DOI: 10.48550/arxiv.2203.04920
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Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It

Abstract: Many fundamental problems affecting the care of critically ill patients lead to similar analytical challenges: physicians cannot easily estimate the effects of at-risk medical conditions or treatments (which is problematic for treatment decisions) because the causal effects of medical conditions and drugs are entangled. They also cannot easily perform studies: there are not enough critically ill patients for high-dimensional observational causal inference analysis, and randomized controlled trials often cannot… Show more

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