From the 1 of 5 linked papers with an AI index.
5 papers
Kernel weighted importance sampling for off-policy evaluation in contextual bandits
Joshua Spear, Matthieu Komorowski, Rebecca Pope +2
The paper introduces Kernel-WIS, a new estimator that uses kernel-weighted importance sampling to evaluate policies offline in contextual bandit settings, offering consistency and…
Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention
Brian D. Williamson, Erica E. M. Moodie, Gregory E. Simon +2
Risk of suicide attempt varies over time. Understanding the importance of risk factors measured at a mental health visit can help clinicians evaluate future risk and provide approp…
A Bayesian adaptive enrichment design using aggregate historical data to inform individualized treatment recommendations
Lara Maleyeff, Shirin Golchi, Erica E. M. Moodie
Adaptive enrichment trials aim to identify and recruit participants most likely to benefit from treatment based on evolving biomarker evidence, with the goal of informing individua…
Doubly-Robust Bayesian Estimation of Optimal Individualized Treatment Rules using Network Meta-Analysis
Augustine Wigle, Erica E. M. Moodie
An optimal individualized treatment rule (ITR) is a function that takes a patient's characteristics, such as demographics, biomarkers, and treatment history, and outputs a treatmen…
Personalized Treatment Hierarchies in Bayesian Network Meta-Analysis
Augustine Wigle, Erica E. M. Moodie
Network Meta-Analysis (NMA) is an increasingly popular evidence synthesis tool that can provide a ranking of competing treatments, also known as a treatment hierarchy. Treatment-Co…