| Estimating individualized treatment rules using outcome weighted learning Y Zhao, D Zeng, AJ Rush, MR Kosorok Journal of the American Statistical Association 107 (499), 1106-1118, 2012 | 952 | 2012 |
| New statistical learning methods for estimating optimal dynamic treatment regimes YQ Zhao, D Zeng, EB Laber, MR Kosorok Journal of the American Statistical Association 110 (510), 583-598, 2015 | 342 | 2015 |
| Tree-based methods for individualized treatment regimes EB Laber, YQ Zhao Biometrika 102 (3), 501-514, 2015 | 245 | 2015 |
| Doubly robust learning for estimating individualized treatment with censored data YQ Zhao, D Zeng, EB Laber, R Song, M Yuan, MR Kosorok Biometrika 102 (1), 151-168, 2015 | 197 | 2015 |
| Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m-Out-of-n Bootstrap Scheme B Chakraborty, EB Laber, Y Zhao Biometrics 69 (3), 714-723, 2013 | 152 | 2013 |
| Regularized outcome weighted subgroup identification for differential treatment effects Y Xu, M Yu, YQ Zhao, Q Li, S Wang, J Shao Biometrics 71 (3), 645-653, 2015 | 111 | 2015 |
| Augmented outcome‐weighted learning for estimating optimal dynamic treatment regimens Y Liu, Y Wang, MR Kosorok, Y Zhao, D Zeng Statistics in medicine 37 (26), 3776-3788, 2018 | 110 | 2018 |
| Efficient augmentation and relaxation learning for individualized treatment rules using observational data YQ Zhao, EB Laber, Y Ning, S Saha, BE Sands Journal of Machine Learning Research 20 (48), 1-23, 2019 | 78 | 2019 |
| 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 | 71 | 2017 |
| Electronic health records and community health surveillance of childhood obesity TL Flood, YQ Zhao, EJ Tomayko, A Tandias, AL Carrel, LP Hanrahan American journal of preventive medicine 48 (2), 234-240, 2015 | 69 | 2015 |
| On sparse representation for optimal individualized treatment selection with penalized outcome weighted learning R Song, M Kosorok, D Zeng, Y Zhao, E Laber, M Yuan Stat 4 (1), 59-68, 2015 | 65 | 2015 |
| Inference about the expected performance of a data-driven dynamic treatment regime B Chakraborty, EB Laber, YQ Zhao Clinical Trials 11 (4), 408-417, 2014 | 64 | 2014 |
| Body image dissatisfaction in patients with inflammatory bowel disease S Saha, YQ Zhao, SA Shah, SD Esposti, S Lidofsky, R Bright, M Law, ... Inflammatory Bowel Diseases 21 (2), 345-352, 2015 | 51 | 2015 |
| Robust hybrid learning for estimating personalized dynamic treatment regimens Y Liu, Y Wang, MR Kosorok, Y Zhao, D Zeng arXiv preprint arXiv:1611.02314, 2016 | 46 | 2016 |
| Multicategory outcome weighted margin-based learning for estimating individualized treatment rules C Zhang, J Chen, H Fu, X He, YQ Zhao, Y Liu Statistica sinica 30, 1857, 2020 | 45 | 2020 |
| Menstrual cycle changes in women with inflammatory bowel disease: a study from the ocean state Crohn's and colitis area registry S Saha, YQ Zhao, SA Shah, SD Esposti, S Lidofsky, S Salih, R Bright, ... Inflammatory bowel diseases 20 (3), 534-540, 2014 | 45 | 2014 |
| Using pilot data to size a two‐arm randomized trial to find a nearly optimal personalized treatment strategy EB Laber, YQ Zhao, T Regh, M Davidian, A Tsiatis, JB Stanford, D Zeng, ... Statistics in medicine 35 (8), 1245-1256, 2016 | 33 | 2016 |
| SWOG S1929: Phase II randomized study of maintenance atezolizumab (A) versus atezolizumab+ talazoparib (AT) in patients with SLFN11 positive extensive stage small cell lung … NF Abdel Karim, J Miao, KL Reckamp, CM Gay, LA Byers, Y Zhao, ... Journal of Clinical Oncology 41 (16_suppl), 8504-8504, 2023 | 31 | 2023 |
| Estimation of optimal dynamic treatment regimes YQ Zhao, EB Laber Clinical Trials 11 (4), 400-407, 2014 | 31 | 2014 |
| Robustifying trial-derived optimal treatment rules for a target population YQ Zhao, D Zeng, CM Tangen, ML Leblanc Electronic journal of statistics 13 (1), 1717, 2019 | 27 | 2019 |
