no code implementations • 13 Dec 2019 • Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen, Michael T. Lawson, Longshaokan Wang, Yunshu Zhang, Eric B. Laber, Yufeng Liu, Jen Jen Yeh, Donglin Zeng, Michael R. Kosorok
PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments.
no code implementations • 5 Feb 2019 • Crystal T. Nguyen, Daniel J. Luckett, Anna R. Kahkoska, Grace E. Shearrer, Donna Spruijt-Metz, Jaimie N. Davis, Michael R. Kosorok
The field of precision medicine aims to tailor treatment based on patient-specific factors in a reproducible way.
no code implementations • 17 Jul 2018 • Daniel J. Luckett, Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, Michael R. Kosorok
We propose a method for constructing confidence bands for the SVM ROC curve and provide the theoretical justification for the SVM ROC curve by showing that the risk function of the estimated decision rule is uniformly consistent across the weight parameter.
no code implementations • 28 Nov 2017 • Daniel J. Luckett, Eric B. Laber, Michael R. Kosorok
Estimated composite outcomes are subsequently used to construct an estimator of an individualized treatment rule which maximizes the mean of patient-specific composite outcomes.
no code implementations • 10 Nov 2016 • Daniel J. Luckett, Eric B. Laber, Anna R. Kahkoska, David M. Maahs, Elizabeth Mayer-Davis, Michael R. Kosorok
However, existing methods for estimating optimal dynamic treatment regimes are designed for a small number of fixed decision points occurring on a coarse time-scale.