Xiangzhou Zhang

According to our database, Xiangzhou Zhang authored at least 26 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Development and validation of a Multi-Causal investigation and discovery framework for knowledge harmonization (MINDMerge): A case study with acute kidney injury risk factor discovery using electronic medical records.

Mingyang Zhang, Xiangzhou Zhang, Mingyang Dai, Lijuan Wu, Kang Liu, Hongnian Wang, Weiqi Chen, Mei Liu, Yong Hu

Int. J. Medical Informatics, 2024

Interpretable subgroup learning-based modeling framework: Study of diabetic kidney disease prediction.

Bo Liu, Xiangzhou Zhang, Kang Liu, Xinhou Hu, Eric W. T. Ngai, Weiqi Chen, Ho Yin Chan, Yong Hu, Mei Liu

Health Informatics J., 2024

2022

A hybrid adaptive approach for instance transfer learning with dynamic and imbalanced data.

Xiangzhou Zhang, Kang Liu, Borong Yuan, Hongnian Wang, Shaoyong Chen, Yunfei Xue, Weiqi Chen, Mei Liu, Yong Hu

Int. J. Intell. Syst., December, 2022

Temporal dynamics of clinical risk predictors for hospital-acquired acute kidney injury under different forecast time windows.

Lijuan Wu, Yong Hu, Xiangzhou Zhang, Borong Yuan, Weiqi Chen, Kang Liu, Mei Liu

Knowl. Based Syst., 2022

Development of a knowledge mining approach to uncover heterogeneous risk predictors of acute kidney injury across age groups.

Lijuan Wu, Yong Hu, Xiangzhou Zhang, Jia Zhang, Mei Liu

Int. J. Medical Informatics, 2022

Characterizing the temporal changes in association between modifiable risk factors and acute kidney injury with multi-view analysis.

Kang Liu, Borong Yuan, Xiangzhou Zhang, Weiqi Chen, Lav P. Patel, Yong Hu, Mei Liu

Int. J. Medical Informatics, 2022

2021

Location Sensitive Network for Human Instance Segmentation.

Xiangzhou Zhang, Bingpeng Ma, Hong Chang, Shiguang Shan, Xilin Chen

IEEE Trans. Image Process., 2021

Novel deep learning-based transcriptome data analysis for drug-drug interaction prediction with an application in diabetes.

Qichao Luo, Shenglong Mo, Yunfei Xue, Xiangzhou Zhang, Yuliang Gu, Lijuan Wu, Jia Zhang, Linyan Sun, Mei Liu, Yong Hu

BMC Bioinform., 2021

2020

Which risk predictors are more likely to indicate severe AKI in hospitalized patients?

Lijuan Wu, Yong Hu, Borong Yuan, Xiangzhou Zhang, Weiqi Chen, Kang Liu, Mei Liu

Int. J. Medical Informatics, 2020

2018

Causal risk factor discovery for severe acute kidney injury using electronic health records.

Weiqi Chen, Yong Hu, Xiangzhou Zhang, Lijuan Wu, Kang Liu, Jianqin He, Zilin Tang, Xing Song, Lemuel R. Waitman, Mei Liu

BMC Medical Informatics Decis. Mak., 2018

2016

Multiple-cause discovery combined with structure learning for high-dimensional discrete data and application to stock prediction.

Weiqi Chen, Zhifeng Hao, Ruichu Cai, Xiangzhou Zhang, Yong Hu, Mei Liu

Soft Comput., 2016

2015

An evolutionary trend reversion model for stock trading rule discovery.

Xiangzhou Zhang, Yong Hu, Kang Xie, Weiguo Zhang, Lijun Su, Mei Liu

Knowl. Based Syst., 2015

iTrade: A Mobile Data-Driven Stock Trading System with Concept Drift Adaptation.

Yong Hu, Xiangzhou Zhang, Bin Feng, Kang Xie, Mei Liu

Int. J. Data Warehous. Min., 2015

Stock trading rule discovery with an evolutionary trend following model.

Yong Hu, Bin Feng, Xiangzhou Zhang, E. W. T. Ngai, Mei Liu

Expert Syst. Appl., 2015

Concept drift mining of portfolio selection factors in stock market.

Yong Hu, Kang Liu, Xiangzhou Zhang, Kang Xie, Weiqi Chen, Yuran Zeng, Mei Liu

Electron. Commer. Res. Appl., 2015

Cost-sensitive and ensemble-based prediction model for outsourced software project risk prediction.

Yong Hu, Bin Feng, Xizhu Mo, Xiangzhou Zhang, E. W. T. Ngai, Ming Fan, Mei Liu

Decis. Support Syst., 2015

Application of evolutionary computation for rule discovery in stock algorithmic trading: A literature review.

Yong Hu, Kang Liu, Xiangzhou Zhang, Lijun Su, E. W. T. Ngai, Mei Liu

Appl. Soft Comput., 2015

2014

A causal feature selection algorithm for stock prediction modeling.

Xiangzhou Zhang, Yong Hu, Kang Xie, Shouyang Wang, E. W. T. Ngai, Mei Liu

Neurocomputing, 2014

Concept Drift Mining of Fundamental Variables in China Stock Market.

Yong Hu, Kang Liu, Bin Feng, Lijun Su, Xiangzhou Zhang, Weiqi Chen, Yuran Zeng

Proceedings of the 2014 Ninth International Conference on P2P, 2014

Discovering Many-to-One Causality in Software Project Risk Analysis.

Weiqi Chen, Kang Liu, Lijun Su, Mei Liu, Zhifeng Hao, Yong Hu, Xiangzhou Zhang

Proceedings of the 2014 Ninth International Conference on P2P, 2014

2013

Software project risk analysis using Bayesian networks with causality constraints.

Yong Hu, Xiangzhou Zhang, E. W. T. Ngai, Ruichu Cai, Mei Liu

Decis. Support Syst., 2013

An integrative framework for intelligent software project risk planning.

Yong Hu, Jianfeng Du, Xiangzhou Zhang, Xiaoling Hao, E. W. T. Ngai, Ming Fan, Mei Liu

Decis. Support Syst., 2013

A Cost-sensitive Intelligent Prediction Model for Outsourced Software Project Risk.

Hongming Zhang, Bin Feng, Xizhu Mo, Lijun Su, Xiangzhou Zhang, Yong Hu

Proceedings of the 12th Wuhan International Conference on E-Business, 2013

A Prediction Model for Stock Market: A Comparison of The World's Top Investors with Data Mining Method.

Yong Hu, Bin Feng, Xiangzhou Zhang, Xin Ying Qiu, Risong Li, Kang Xie

Proceedings of the 12th Wuhan International Conference on E-Business, 2013

iTrade: An Adaptive Risk-Adjusted Intelligent Stock Trading System from the Perspective of Concept Drift.

Yong Hu, Bin Feng, Xiangzhou Zhang, Kang Liu, Kang Xie, Mei Liu

Proceedings of the 2013 Fourth International Conference on Emerging Intelligent Data and Web Technologies, 2013

2012

Intelligent Analysis Model for Outsourced Software Project Risk Using Constraint-based Bayesian Network.

Yong Hu, Xizhu Mo, Xiangzhou Zhang, Yuran Zeng, Jianfeng Du, Kang Xie

J. Softw., 2012