Reinforcement learning trees R Zhu, D Zeng, MR Kosorok Journal of the American Statistical Association 110 (512), 1770-1784, 2015 | 224 | 2015 |
Lung epithelial and endothelial damage, loss of tissue repair, inhibition of fibrinolysis, and cellular senescence in fatal COVID-19 F D’Agnillo, KA Walters, Y Xiao, ZM Sheng, K Scherler, J Park, S Gygli, ... Science translational medicine 13 (620), eabj7790, 2021 | 183 | 2021 |
Recursively imputed survival trees R Zhu, MR Kosorok Journal of the American Statistical Association 107 (497), 331-340, 2012 | 95 | 2012 |
Combining biomarkers with EMR data to identify patients in different phases of sepsis I Taneja, B Reddy, G Damhorst, S Dave Zhao, U Hassan, Z Price, ... Scientific reports 7 (1), 10800, 2017 | 82 | 2017 |
Greedy outcome weighted tree learning of optimal personalized treatment rules R Zhu, YQ Zhao, G Chen, S Ma, H Zhao Biometrics 73 (2), 391-400, 2017 | 67 | 2017 |
Tree based weighted learning for estimating individualized treatment rules with censored data Y Cui, R Zhu, M Kosorok Electronic journal of statistics 11 (2), 3927, 2017 | 65 | 2017 |
Estimating heterogeneous treatment effects with right-censored data via causal survival forests Y Cui, MR Kosorok, E Sverdrup, S Wager, R Zhu Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023 | 64 | 2023 |
CONSISTENCY OF SURVIVAL TREE AND FOREST MODELS Y Cui, R Zhu, M Zhou, M Kosorok Statistica Sinica 32 (3), 1245-1267, 2022 | 40* | 2022 |
Integrating multidimensional omics data for cancer outcome R Zhu, Q Zhao, H Zhao, S Ma Biostatistics 17 (4), 605-618, 2016 | 40 | 2016 |
Increasing access to state psychiatric hospital beds: exploring supply-side solutions EM La, KH Lich, R Wells, AR Ellis, MS Swartz, R Zhu, JP Morrissey Psychiatric Services 67 (5), 523-528, 2016 | 40 | 2016 |
Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer R Miao, TC Badger, K Groesch, PL Diaz-Sylvester, T Wilson, A Ghareeb, ... PLoS One 15 (1), e0227707, 2020 | 38 | 2020 |
Bagging and deep learning in optimal individualized treatment rules X Mi, F Zou, R Zhu Biometrics 75 (2), 674-684, 2019 | 35 | 2019 |
Fecal bacteria as biomarkers for predicting food intake in healthy adults LM Shinn, Y Li, A Mansharamani, LS Auvil, ME Welge, C Bushell, ... The Journal of nutrition 151 (2), 423-433, 2021 | 32 | 2021 |
Estimating optimal infinite horizon dynamic treatment regimes via pt-learning W Zhou, R Zhu, A Qu Journal of the American Statistical Association 119 (545), 625-638, 2024 | 27 | 2024 |
Risk assessment of latent tuberculosis infection through a multiplexed cytokine biosensor assay and machine learning feature selection HM Robison, CA Chapman, H Zhou, CL Erskine, E Theel, T Peikert, ... Scientific reports 11 (1), 20544, 2021 | 26 | 2021 |
Efficient gradient boosting for prognostic biomarker discovery K Li, S Yao, Z Zhang, B Cao, CM Wilson, D Kalos, PF Kuan, R Zhu, ... Bioinformatics 38 (6), 1631-1638, 2022 | 24 | 2022 |
Constructing dynamic treatment regimes with shared parameters for censored data YQ Zhao, R Zhu, G Chen, Y Zheng Statistics in medicine 39 (9), 1250-1263, 2020 | 21* | 2020 |
Topic modeling on triage notes with semiorthogonal nonnegative matrix factorization Y Li, R Zhu, A Qu, H Ye, Z Sun Journal of the American Statistical Association 116 (536), 1609-1624, 2021 | 20* | 2021 |
Diagnostic and prognostic capabilities of a biomarker and EMR‐based machine learning algorithm for sepsis I Taneja, GL Damhorst, C Lopez‐Espina, SD Zhao, R Zhu, S Khan, ... Clinical and translational science 14 (4), 1578-1589, 2021 | 16 | 2021 |
Identifying gene–environment and gene–gene interactions using a progressive penalization approach R Zhu, H Zhao, S Ma Genetic epidemiology 38 (4), 353-368, 2014 | 16 | 2014 |