Multiple kernel learning and the SMO algorithm Z Sun, N Ampornpunt, M Varma, S Vishwanathan Advances in neural information processing systems 23, 2010 | 226 | 2010 |
Boosting deep learning risk prediction with generative adversarial networks for electronic health records Z Che, Y Cheng, S Zhai, Z Sun, Y Liu 2017 IEEE International Conference on Data Mining (ICDM), 787-792, 2017 | 188 | 2017 |
Exploiting convolutional neural network for risk prediction with medical feature embedding Z Che, Y Cheng, Z Sun, Y Liu arXiv preprint arXiv:1701.07474, 2017 | 66 | 2017 |
DPVis: Visual analytics with hidden markov models for disease progression pathways BC Kwon, V Anand, KA Severson, S Ghosh, Z Sun, BI Frohnert, ... IEEE transactions on visualization and computer graphics 27 (9), 3685-3700, 2020 | 62 | 2020 |
Early prediction of diabetes complications from electronic health records: A multi-task survival analysis approach B Liu, Y Li, Z Sun, S Ghosh, K Ng Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 43 | 2018 |
A probabilistic disease progression modeling approach and its application to integrated Huntington’s disease observational data Z Sun, S Ghosh, Y Li, Y Cheng, A Mohan, C Sampaio, J Hu JAMIA open 2 (1), 123-130, 2019 | 41 | 2019 |
Systematic comparison of RNA-Seq normalization methods using measurement error models Z Sun, Y Zhu Bioinformatics 28 (20), 2584-2591, 2012 | 36 | 2012 |
Quantification of uncertainty in estimated nitrate-N loads in agricultural watersheds Y Jiang, JR Frankenberger, LC Bowling, Z Sun Journal of Hydrology 519, 106-116, 2014 | 29 | 2014 |
Complication risk profiling in diabetes care: A Bayesian multi-task and feature relationship learning approach B Liu, Y Li, S Ghosh, Z Sun, K Ng, J Hu IEEE Transactions on Knowledge and Data Engineering 32 (7), 1276-1289, 2019 | 26 | 2019 |
A machine‐learning derived Huntington's disease progression model: insights for clinical trial design A Mohan, Z Sun, S Ghosh, Y Li, S Sathe, J Hu, C Sampaio Movement Disorders 37 (3), 553-562, 2022 | 24 | 2022 |
LINKAGE: An approach for comprehensive risk prediction for care management Z Sun, F Wang, J Hu Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 18 | 2015 |
Bayesian inference with historical data-based informative priors improves detection of differentially expressed genes B Li, Z Sun, Q He, Y Zhu, ZS Qin Bioinformatics 32 (5), 682-689, 2016 | 14 | 2016 |
An exploration of latent structure in observational Huntington’s disease studies S Ghosh, Z Sun, Y Li, Y Cheng, A Mohan, C Sampaio, J Hu AMIA Summits on Translational Science Proceedings 2017, 92, 2017 | 10 | 2017 |
Data-Driven Prediction of Beneficial Drug Combinations in Spontaneous Reporting Systems Y Li, P Zhang, Z Sun, J Hu American Medical Informatics Association Summit on Clinical Research …, 2016 | 10 | 2016 |
A data-driven method for generating robust symptom onset indicators in Huntington’s disease registry data Z Sun, Y Li, S Ghosh, Y Cheng, A Mohan, C Sampaio, J Hu AMIA Annual Symposium Proceedings 2017, 1635, 2017 | 8 | 2017 |
Data-driven prediction of drug combinations that mitigate adverse drug reactions J Hu, Y Li, Z Sun, P Zhang US Patent 10,490,301, 2019 | 7 | 2019 |
G-computation and hierarchical models for estimating multiple causal effects from observational disease registries with irregular visits Z Shahn, Y Li, Z Sun, A Mohan, C Sampaio, J Hu AMIA Summits on Translational Science Proceedings 2019, 789, 2019 | 7 | 2019 |
From good to great: nonlinear improvement of healthcare service S Liu, J Chen, Z Sun, MY Zhu International Journal of Pharmaceutical and Healthcare Marketing 12 (4), 391-408, 2018 | 6 | 2018 |
Deep state space models for computational phenotyping S Ghosh, Y Cheng, Z Sun 2016 IEEE international conference on healthcare informatics (ICHI), 399-402, 2016 | 6 | 2016 |
Method for proactive comprehensive geriatric risk screening J Hu, Z Sun, F Wang US Patent 10,535,424, 2020 | 5 | 2020 |