Zhaonan Sun
Zhaonan Sun
IBM Research
Verified email at us.ibm.com - Homepage
Cited by
Cited by
Multiple kernel learning and the SMO algorithm
Z Sun, N Ampornpunt, M Varma, S Vishwanathan
Advances in neural information processing systems 23, 2361-2369, 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
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
Systematic comparison of RNA-Seq normalization methods using measurement error models
Z Sun, Y Zhu
Bioinformatics 28 (20), 2584-2591, 2012
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
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
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
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
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
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, 2020
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
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
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
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
Evidence boosting in rational drug design and indication expansion by leveraging disease association
J Hu, Z Sun, F Wang, P Zhang
US Patent 10,839,936, 2020
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
Statistical Calibration of qRT-PCR, Microarray and RNA-Seq Gene Expression Data with Measurement Error Models
Z Sun, T Kuczek, Y Zhu
Annals of Applied Statistics, 2014
Simultaneous modeling of multiple complications for risk profiling in diabetes care
B Liu, Y Li, S Ghosh, Z Sun, K Ng, J Hu
arXiv preprint arXiv:1802.06476, 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
Comparison on confidence bands of decision boundary between SVM and Logistic Regression
X Wang, X Wang, Z Sun
2009 Fifth International Joint Conference on INC, IMS and IDC, 272-277, 2009
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