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From the 1 of 12 linked papers with an AI index.

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20242026
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stat.ME2026

Backward Bayesian Outcome Weighted Learning

Emmanuel M. Rockwell, Michael R. Kosorok, Nikki L. B. Freeman

A central objective of precision medicine is learning optimal dynamic treatment regimes (DTRs) from data. Classification-based methods, like outcome weighted learning (OWL) for sin…

stat.ME2026

Bayesian Mediation Analysis for Individualized Treatment Rules

Emmanuel M. Rockwell, Patrick J. Smith, Michael R. Kosorok +1

The value of an individualized treatment rule (ITR), defined as the expected outcome under treatment assignment according to the rule, is useful for assessing average clinical bene…

stat.ME2026

A Review of Methods and Practices for Missing Data in Sequential Multiple Assignment Randomized Trials (SMARTs): An Ancillary Study of a Scoping Review

Nikki L. B. Freeman, Chenyao Yu, Margaret Hoch +5

Background: Missing data poses an acute threat to sequential multiple assignment randomized trial (SMART) analyses because of the sequential treatment structure and response-depend…

stat.ME2026

Distributional Random Forests for Complex Survey Designs

Yating Zou, Marcos Matabuena, Michael R. Kosorok

We study estimation of the conditional law and continuous measurable maps of it when takes values in a locally compact Polish space (e.g., $\mathbb…

stat.ME2025

Confidence Regions for Multiple Outcomes, Effect Modifiers, and Other Multiple Comparisons

Paul N Zivich, Stephen R Cole, Noah Greifer +3

In epidemiology, some have argued that multiple comparison corrections are not necessary as there is rarely interest in the universal null hypothesis. From a parameter estimation p…

stat.ME2025

Medical Knowledge Integration into Reinforcement Learning Algorithms for Dynamic Treatment Regimes

Sophia Yazzourh, Nicolas Savy, Philippe Saint-Pierre +1

The goal of precision medicine is to provide individualized treatment at each stage of chronic diseases, a concept formalized by Dynamic Treatment Regimes (DTR). These regimes adap…