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Found 7 papers, 1 papers with code
Pragmatic Clinical Trials in the Rubric of Structural Causal Models
Explanatory studies, such as randomized controlled trials, are targeted to extract the true causal effect of interventions on outcomes and are by design adjusted for covariates through randomization.
CKH: Causal Knowledge Hierarchy for Estimating Structural Causal Models from Data and Priors
Using CKH, we present a methodological framework for encoding causal priors from various information sources and combining them to derive an SCM.
Causal Discovery on the Effect of Antipsychotic Drugs on Delirium Patients in the ICU using Large EHR Dataset
To explore safety outcomes associated with APD, we aim to build a causal model for delirium in the ICU using large observational data sets connecting various covariates correlated with delirium.
Structural Causal Model with Expert Augmented Knowledge to Estimate the Effect of Oxygen Therapy on Mortality in the ICU
Recent advances in causal inference techniques, more specifically, in the theory of structural causal models, provide the framework for identification of causal effects from observational data in the cases where the causal graph is identifiable, i. e., the data generating mechanism can be recovered from the joint distribution.
Identifying and Analyzing Sepsis States: A Retrospective Study on Patients with Sepsis in ICUs
Sepsis accounts for more than 50% of hospital deaths, and the associated cost ranks the highest among hospital admissions in the US.
Development of an Algorithm for Identifying Changes in System Dynamics from Time Series
The development of an algorithm with related mathematical concepts and supporting hypothesis for detecting changes in system dynamics from time series along with empirical analysis and theoretical justification is presented.
A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal Model
Randomized controlled trials (RCTs) are considered the gold standard for identifying causal relationships.
