Michael R Kosorok

发表

Estimating Individualized Treatment Rules Using Outcome Weighted Learning

Donglin Zeng, Yingqi Zhao, A John Rush, 2012, Journal of the American Statistical Association.

Discussion of combining biomarkers to optimize patient treatment recommendations

Michael R Kosorok, Ying-Qi Zhao, M. Kosorok, 2014, Biometrics.

Prospects and challenges for clinical decision support in the era of big data.

Michael R Kosorok, Issam El Naqa, Judy Jin, 2018, JCO clinical cancer informatics.

THE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS.

Hao Zhu, Fei Zou, Michael R Kosorok, 2012, Journal of statistical research.

Detecting Disease Outbreaks Using Local Spatiotemporal Methods

Amy Ising, Donglin Zeng, Yingqi Zhao, 2011, Biometrics.

On Brownian Distance Covariance and High Dimensional Data.

Michael R Kosorok, 2009, The annals of applied statistics.

An extended proportional hazards model for interval-censored data subject to instantaneous failures

Michael R Kosorok, Christopher S McMahan, Prabhashi W Withana Gamage, 2019, Lifetime Data Analysis.

Personalized Dose Finding Using Outcome Weighted Learning

Donglin Zeng, Michael R Kosorok, Guanhua Chen, 2016, Journal of the American Statistical Association.

FEATURE ELIMINATION IN KERNEL MACHINES IN MODERATELY HIGH DIMENSIONS.

Yair Goldberg, Michael R Kosorok, Sayan Dasgupta, 2013, Annals of statistics.

Residual Weighted Learning for Estimating Individualized Treatment Rules

Michael R Kosorok, Umer Khan, Xin Zhou, 2015, Journal of the American Statistical Association.

New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes

Donglin Zeng, Michael R Kosorok, Eric B. Laber, 2015, Journal of the American Statistical Association.

Discussion of Laber et al. "Optimal treatment allocations in space and time for on-line control of an emerging infectious disease".

Yifan Cui, Michael R Kosorok, Hunyong Cho, 2018, Journal of the Royal Statistical Society. Series C, Applied statistics.

Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction.

Yufeng Liu, Chong Zhang, Michael R Kosorok, 2017, Statistics and its interface.

Robust semiparametric microarray normalization and significance analysis.

Jian Huang, Shuangge Ma, Hehuang Xie, 2006, Biometrics.

On the Use of Optimal Transportation Theory to Recode Variables and Application to Database Merging

Michael R Kosorok, Benoit Lepage, Chloé Dimeglio, 2019, The international journal of biostatistics.

Augmented outcome‐weighted learning for estimating optimal dynamic treatment regimens

Ying Liu, Donglin Zeng, Yingqi Zhao, 2018, Statistics in medicine.

Estimating individualized treatment rules for ordinal treatments

Yufeng Liu, Haoda Fu, Michael R Kosorok, 2017, Biometrics.

Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules

Michael R Kosorok, Eric B. Laber, Eric B Laber, 2018, Biometrics.

On semiparametric efficient inference for two-stage outcome-dependent sampling with a continuous outcome.

Michael R Kosorok, Haibo Zhou, Rui Song, 2009, Biometrika.

Multistate recursively imputed survival trees for time-to-event data analysis: an application to AIDS and mortality post-HIV infection data

Michael R Kosorok, Leili Tapak, Omid Hamidi, 2018, BMC Medical Research Methodology.

Comment on "Dynamic treatment regimes: technical challenges and applications"

Donglin Zeng, Yair Goldberg, Michael R Kosorok, 2014, Electronic journal of statistics.

Multi-threshold Change Plane Model: Estimation Theory and Applications in Subgroup Identification

Jialiang Li, Michael R Kosorok, Baisuo Jin, 2018, 1808.00647.

Developing Adaptive Personalized Therapy for Cystic Fibrosis using Reinforcement Learning

Michael R Kosorok, M. Kosorok, Yiyun Tang, 2012 .

Using pilot data to size a two‐arm randomized trial to find a nearly optimal personalized treatment strategy

Rui Song, Donglin Zeng, Marie Davidian, 2016, Statistics in medicine.

What's So Special About Semiparametric Methods?

Michael R Kosorok, M. Kosorok, 2009, Sankhya. Series B. [Methodological.].

Additive Risk Models for Survival Data with High‐Dimensional Covariates

Shuangge Ma, Michael R Kosorok, Jason P Fine, 2006, Biometrics.

Simultaneous Inferences on the Contrast of Two Hazard Functions with Censored Observations

Michael R Kosorok, Peter B Gilbert, John D Clemens, 2002, Biometrics.

Latent Supervised Learning

Michael R Kosorok, Susan Wei, M. Kosorok, 2013, Journal of the American Statistical Association.

Reproducibility of a Scoring System for Computed Tomography Scanning in Cystic Fibrosis

Michael R Kosorok, M. Kosorok, L. S. Broderick, 2006, Journal of thoracic imaging.

Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis

Jian Huang, Shuangge Ma, Michael R Kosorok, 2011, BMC Medical Genomics.

Recursively Imputed Survival Trees

Michael R Kosorok, Ruoqing Zhu, M. Kosorok, 2012, Journal of the American Statistical Association.

Nonparametric Association Analysis of Bivariate Competing-Risks Data

Yu Cheng, Michael R Kosorok, Jason P Fine, 2007 .

Design and Analysis of Group Sequential Clinical Trials with Multiple Primary Endpoints

Michael R Kosorok, David L DeMets, M. Kosorok, 2004, Biometrics.

A framework for understanding cancer comparative effectiveness research data needs.

Amy P Abernethy, Michael R Kosorok, Til Stürmer, 2012, Journal of clinical epidemiology.

Reinforcement Learning Trees

Donglin Zeng, Michael R Kosorok, Ruoqing Zhu, 2015, Journal of the American Statistical Association.

Simultaneous Critical Values For T-Tests In Very High Dimensions.

Michael R Kosorok, Hongyuan Cao, M. Kosorok, 2011, Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability.