The results presented here on S. cerevisiae and the DREAM4 data are proof-of-concept results that IDA can predict the strongest causal effects in potentially large-scale biological systems by ...

The goal of many observational epidemiological studies is to make causal inferences about the effects of interventions or exposures on health outcomes. This course defines causation in biomedical ...

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There is substantial interest in using urgent care centers to decrease lower-acuity emergency department (ED) visits. Using 2008–19 insurance claims and enrollment data from a national managed ...

Traditional domain-specific causal discovery relies on expert knowledge to guide the data-based structure learning process, thereby improving the reliability of recovered causality. Recent studies ...

We also see existing causal methods as promising tools for LLMs to formalize, validate, and communicate their reasoning especially in high-stakes scenarios. In capturing common sense and domain ...