| Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ... Cell 184 (8), 2239-2254. e39, 2021 | 336 | 2021 |
| Principal weighted support vector machines for sufficient dimension reduction in binary classification SJ Shin, Y Wu, HH Zhang, Y Liu Biometrika 104 (1), 67-81, 2017 | 45 | 2017 |
| Probability‐enhanced sufficient dimension reduction for binary classification SJ Shin, Y Wu, HH Zhang, Y Liu Biometrics 70 (3), 546-555, 2014 | 34 | 2014 |
| Penetrance of Different Cancer Types in Families with Li-Fraumeni Syndrome: A Validation Study Using Multicenter CohortsCancer-Specific Penetrance in LFS SJ Shin, EB Dodd-Eaton, G Peng, J Bojadzieva, J Chen, CI Amos, ... Cancer research 80 (2), 354-360, 2020 | 30 | 2020 |
| Penalized principal logistic regression for sparse sufficient dimension reduction SJ Shin, A Artemiou Computational Statistics & Data Analysis 111, 48-58, 2017 | 22 | 2017 |
| Real-time sufficient dimension reduction through principal least squares support vector machines A Artemiou, Y Dong, SJ Shin Pattern Recognition 112, 107768, 2021 | 18 | 2021 |
| Principal quantile regression for sufficient dimension reduction with heteroscedasticity C Wang, SJ Shin, Y Wu Electronic Journal of Statistics 12 (2), 2114-2140, 2018 | 16 | 2018 |
| Principal weighted logistic regression for sufficient dimension reduction in binary classification B Kim, SJ Shin Journal of the Korean Statistical Society 48 (2), 194-206, 2019 | 15 | 2019 |
| Bayesian estimation of a semiparametric recurrent event model with applications to the penetrance estimation of multiple primary cancers in Li-Fraumeni Syndrome J Li, SJ Shin, J Ning, J Bojadzieva, LC Strong, W Wang arXiv preprint arXiv:1804.06883, 2018 | 12* | 2018 |
| Two-dimensional solution surface for weighted support vector machines SJ Shin, Y Wu, HH Zhang Journal of Computational and Graphical Statistics 23 (2), 383-402, 2014 | 12 | 2014 |
| Penetrance Estimates Over Time to First and Second Primary Cancer Diagnosis in Families with Li-Fraumeni Syndrome: A Single Institution PerspectiveMultiple Primary Cancer … SJ Shin, EB Dodd-Eaton, F Gao, J Bojadzieva, J Chen, X Kong, CI Amos, ... Cancer research 80 (2), 347-353, 2020 | 11 | 2020 |
| Bayesian Semiparametric Estimation of Cancer-specific Age-at-onset Penetrance with Application to Li-Fraumeni Syndrome SJ Shin, Y Yuan, LC Strong, J Bojadzieva, W Wang Journal of the American Statistical Association, 1-32, 2018 | 10 | 2018 |
| Association between in vitro fertilization success rate and ambient air pollution: a possible explanation of within-year variation of in vitro fertilization success rate J Kang, JY Lee, H Song, SJ Shin, J Kim Obstetrics & Gynecology Science 63 (1), 72-79, 2020 | 9 | 2020 |
| A nonparametric survival function estimator via censored kernel quantile regressions SJ Shin, HH Zhang, Y Wu Statistica Sinica, 457-478, 2017 | 7 | 2017 |
| A forward approach for sufficient dimension reduction in binary classification J Kang, SJ Shin Journal of Machine Learning Research 23 (199), 1-31, 2022 | 5 | 2022 |
| Quantile-slicing estimation for dimension reduction in regression H Kim, Y Wu, SJ Shin Journal of Statistical Planning and Inference 198, 1-12, 2019 | 5 | 2019 |
| Stability approach to selecting the number of principal components J Song, SJ Shin Computational Statistics 33 (4), 1923-1938, 2018 | 5 | 2018 |
| A comparative study of the dose-response analysis with application to the target dose estimation SJ Shin, SK Ghosh Journal of Statistical Theory and Practice 11, 145-162, 2017 | 5 | 2017 |
| Principal weighted least square support vector machine: An online dimension-reduction tool for binary classification HJ Jang, SJ Shin, A Artemiou Computational Statistics & Data Analysis 187, 107818, 2023 | 4 | 2023 |
| The regularization paths for the ROC-optimizing support vector machines D Kim, SJ Shin Journal of the Korean Statistical Society 49 (1), 264-275, 2020 | 4 | 2020 |
