From the 1 of 11 linked papers with an AI index.
11 papers
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…
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…
The Fidelity and Feedback Traps: The Case for Health Digital Twins as Modular Evolving Causal Systems
Nikki L. B. Freeman, Yating Zou, Kyungbok Lee +3
The paper examines pitfalls of using digital twins in healthcare, such as over‑reliance on model accuracy (fidelity trap) and biased updates from self‑generated data (feedback trap…
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…
Linear Regression Using Principal Components from General Hilbert-Space-Valued Covariates
Xinyi Li, Margaret Hoch, Michael R. Kosorok
We introduce Adaptive Subspace PCA (AS-PCA), a framework for principal component analysis of random elements in a general separable Hilbert space. AS-PCA projects the covariance op…
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…