# indicates I am the co-first author. 

* indicates I am the corresponding author.

2025

• Aryeh Zolin, Hwai Ooi, Manqi Zhou, Chang Su, Fei Wang, Harini Sarva. Liver fibrosis associated with more severe motor deficits in early Parkinson’s disease. Clinical Neurology and Neurosurgery. [paper]

• Zhou M, Tang AS, Zhang H, Xu Z, Ke AM, Su C, Huang Y, Mantyh WG, Jaffee MS, Rankin KP, DeKosky ST. Identifying progression subphenotypes of Alzheimer’s disease from large-scale electronic health records with machine learning. Journal of Biomedical Informatics. [paper]

• Aryeh Zolin, Hwai Ooi, Manqi Zhou, Chang Su, Fei Wang, Harini Sarva. Association of Liver Fibrosis with Motor Deficits in Parkinson’s Disease (P2-5.020). In Neurology 2025. [abstract]

• Lijun Dou, Zhenxing Xu, Jielin Xu, Chengxi Zang, Chang Su, Andrew A. Pieper, James B. Leverenz, Fei Wang, Xiongwei Zhu, Jeffrey Cummings & Feixiong Cheng. A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease. npj Parkinson's Disease. [paper]

• Jielin Xu, Wenqiang Song, Zhenxing Xu, Michael M. Danziger, Ehud Karavani, Chengxi Zang, Xin Chen, Yichen Li, Isabela M Rivera Paz, Dhruv Gohel, Chang Su, Yadi Zhou, Yuan Hou, Yishai Shimoni, Andrew A. Pieper, Jianying Hu, Fei Wang, Michal Rosen-Zvi, James B. Leverenz, Jeffrey Cummings, Feixiong Cheng. Single‐microglia transcriptomic transition network‐based prediction and real‐world patient data validation identifies ketorolac as a repurposable drug for Alzheimer's disease. Alzheimer's & Dementia. [paper]

2024

• Chang Su, Yu Hou, Jielin Xu, Zhenxing Xu, Manqi Zhou, Alison Ke, Haoyang Li, Jie Xu, Matthew Brendel, Jacqueline R. M. A. Maasch, Zilong Bai, Haotan Zhang, Yingying Zhu, Molly C. Cincotta, Xinghua Shi, Claire Henchcliffe, James B. Leverenz, Jeffrey Cummings, Michael S. Okun, Jiang Bian, Feixiong Cheng, Fei Wang. Identification of Parkinson’s disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. npj Digital Medicine. [paper]

• Qiannan Zhang, Weishen Pan, Zilong Bai, Chang Su, Fei Wang. Unified Insights: Harnessing Multi-modal Data for Phenotype Imputation via View Decoupling. Advances in Neural Information Processing Systems (NeurIPS) 2024. [paper]

• Yongkang Xiao, Yu Hou, Huixue Zhou, Gayo Diallo, Marcelo Fiszman, Julian Wolfson, Li Zhou, Halil Kilicoglu, You Chen, Chang Su, Hua Xu, William G Mantyh, Rui Zhang. Repurposing non-pharmacological interventions for Alzheimer's disease through link prediction on biomedical literature. Scientific reports. [paper]

• Xue-Yan He, Yuan Gao, David Ng, Evdokia Michalopoulou, Shanu George, Jose M Adrover, Lijuan Sun, Jean Albrengues, Juliane Daßler-Plenker, Xiao Han, Ledong Wan, Xiaoli S Wu, Longling S Shui, Yu-Han Huang, Bodu Liu, Chang Su, David L Spector, Christopher R Vakoc, Linda VanAelst, Mikala Egeblad. Chronic stress causes metastasis via neutrophil-mediated changes to the microenvironment. Cancel Cell. [paper]

• Marianne Arriola, Weishen Pan, Manqi Zhou, Qiannan Zhang, Chang Su, Fei Wang. Joint Analysis of Single-Cell Data across Cohorts with Missing Modalities.  [arxiv]

2023

• Yunyu Xiao, J. John Mann, Julian Chun-Chung Chow, Timothy T. Brown, Lonnie R. Snowden,  Paul Siu-Fai Yip, Alexander C. Tsai, Yu Hou, Jyotishman Pathak, Fei Wang, Chang Su*. Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health. JAMA Pediatrics. [paper]

• Chang Su, Yu Hou, Manqi Zhou, Suraj Rajendran, Jacqueline RMA Maasch, Zehra Abedi, Haotan Zhang, Zilong Bai, Anthony Cuturrufo, Winston Guo, Fayzan F Chaudhry, Gregory Ghahramani, Jian Tang, Feixiong Cheng, Yue Li, Rui Zhang, Steven T DeKosky, Jiang Bian, Fei Wang. Biomedical discovery through the integrative biomedical knowledge hub (iBKH). iScience. [paper] [iBKH] [GitHub]

• Chang Su*, Yu Hou, Michael Levin, Rui Zhang, Fei Wang. Protocol to implement a computational pipeline for biomedical discovery based on a biomedical knowledge graph. STAR Protocols. [paper] [GitHub]

• Zhenxing Xu, Veer Vekaria, Fei Wang, Judith Cukor, Chang Su, Prakash Adekkanattu, Pascal Brandt, Guoqian Jiang, Richard C Kiefer, Yuan Luo, Luke V Rasmussen, Jie Xu, Yunyu Xiao, George Alexopoulos, Jyotishman Pathak. Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records. Psychiatric Research and Clinical Practice. [paper]

2022

• Matthew Brendel, Chang Su#*, Zilong Bai, Hao Zhang, Olivier Elemento, Fei Wang. Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review. Genomics, Proteomics & Bioinformatics. [paper]

• Jay S Patel, Chang Su#, Marisol Tellez, Jasim M Albandar, Rishi Rao, Vishnu Iyer, Evan Shi, Huanmei Wu. Developing and testing a prediction model for periodontal disease using machine learning and big electronic dental record data. Frontiers in Artificial Intelligence. [paper]

• Chang Su, Yu Hou, Fei Wang. GNN-based Biomedical Knowledge Graph Mining in Drug Development. In: Graph Neural Networks: Foundations, Frontiers, and Applications. Springer, Singapore. [Chapter]

• Zhenxing Xu, Chengsheng Mao, Chang Su, Hao Zhang, Ilias Siempos, Lisa K Torres, Di Pan, Yuan Luo, Edward J Schenck, Fei Wang. Sepsis subphenotyping based on organ dysfunction trajectory. Critical Care. [paper]

• Xinyue Hu, Lin Gu, Liangchen Liu, Ruijiang Li, Chang Su, Tatsuya Harada, Yingying Zhu. Memory Efficient Temporal & Visual Graph Model for Unsupervised Video Domain Adaptation. [arxiv]

2021

• Chang Su, Yongkang Zhang, James H Flory, Mark G Weiner, Rainu Kaushal, Edward J Schenck, Fei Wang. Clinical subphenotypes in COVID-19: derivation, validation, prediction, temporal patterns, and interaction with social determinants of health. npj Digital Medicine. [paper]

• Chang Su, Zhenxing Xu, Katherine Hoffman, Parag Goyal, Monika M Safford, Jerry Lee, Sergio Alvarez-Mulett, Luis Gomez-Escobar, David R Price, John S Harrington, Lisa K Torres, Fernando J Martinez, Thomas R. Campion, Rainu Kaushal, Augustine M.K. Choi, Fei Wang, Edward J. Schenck. Identifying organ dysfunction trajectory-based subphenotypes in critically ill patients with COVID-19. Nature Scientific Reports. [medrxiv][paper]

• Chang Su, Katherine Hoffman, Zhenxing Xu, Elizabeth Sanchez, Ilias Siempos, John S Harrington, Alexandra Racanelli, Maria Plataki, Fei Wang, Edward J Schenck. Evaluation of albumin kinetics in mechanically ventilated patients with COVID-19 compared to those with sepsis-induced ARDS. Criti-cal Care Explorations. [medrxiv] [paper]

• # Wanwan Xu, Chang Su, Yan Li, Steven Rogers, Fei Wang, Kun Chen, and Robert Aseltine. Improving suicide risk prediction via targeted data fusion: proof of concept using medical claims data. JAMIA. [paper]

• Matthew Brendel, Chang Su, Yu Hou, Claire Henchcliffe, Fei Wang. Comprehensive subtyping of Parkinson’s disease patients with similarity fusion: a case study with BioFIND data. npj Parkinson's Disease. [paper]

• Zhenxing Xu, Chang Su, Yunyu Xiao, Fei Wang.  Artificial intelligence for COVID-19: Battling the pandemic withcomputational intelligence. Intelligent Medicine. [paper]

• Jie Xu, Benjamin S. Glicksberg, Chang Su, Peter Walker, Jiang Bian, Fei Wang. Federated learning for healthcare informatics. Journal of Healthcare Informatics Research. [paper]

• Zhenxing Xu, Chengsheng Mao, Chang Su, Ilias Siempos, Lisa K Torres, Di Pan, Yuan Luo, Edward J Schenck, Fei Wang. Sepsis Subphenotyping Based on Organ Dysfunction Trajectory. [medrxiv]

• Yunbo Cui, Youtian Du, Xue Wang, Hang Wang, Chang Su. Leveraging attention-based visual clue extraction for image classification. IET Imaging Processing. [paper]

2020

• Chang Su, Robert Aseltine, Riddhi Doshi, Kun Chen, Steven C. Rogers, Fei Wang. Machine learning for suicide risk prediction in children and adolescents with electronic health records. Nature Translational Pyschiatry. [paper]

• Chang Su, Jie Tong, Fei Wang. Mining genetic and transcriptomic data using machine learning approaches in Parkinson’s disease. npj Parkinson's Disease. [paper]

• Chang Su, Zhenxing Xu, Jyotishman Pathak, Fei Wang (2020). Deep learning in mental health outcome research: a scoping review. Nature Translational Pyschiatry. [paper] [pdf]

• Sendong Zhao, Chang Su, Zhiyong Lu, Fei Wang (2020). Recent advances in biomedical literature mining. Briefings in Bioinformatics. [paper]

• Weishen Pan, Chang Su, Kun Chen, Claire Henchcliffe, Fei Wang (2020). Learning Phenotypic Associations for Parkinson's Disease with Longitudinal Clinical Records. medRxiv. [paper]

• Sendong Zhao, Yong Huang, Chang Su, Yuantong Li, Fei Wang (2020). Interactive Attention Networks for Semantic Text Matching. IEEE International Conference on Data Mining (ICDM). [paper]

• Yongjun Zhu, Chao Che, Bo Jin, Ningrui Zhang, Chang Su, Fei Wang. Knowledge-driven drug repurposing using a comprehensive drug knowledge graph. Health Informatics Journal. [paper]

• Hang Wang, Youtian Du, Guangxun Zhang, Zhongmin Cai, Chang Su. Learning Fundamental Visual Concepts Based on Evolved Multi-Edge Concept Graph. IEEE Transactions on Multimedia. [paper]

2019

• Youtian Du, Xue Wang, Yunbo Cui, Hang Wang, Chang Su (2019). Kernel-based Mixture Mapping for Image and Text Association. IEEE Transactions on Multimedia.

• Sendong Zhao, Chang Su, Andera Sboner, Fei Wang (2019). GRAPHENE: A Precise Biomedical Literature Retrieval Engine with Graph Augmented Deep Learning and External Knowledge Empowerment. InProceedings of the 28th ACM International Conference on Information and Knowledge Management 2019 Nov 3 (pp. 149-158).

• Xue Wang, Youtian Du, Xuelian Li, Fuyuan Cao, Chang Su (2019). Embedded Representation of Relation Words with Visual Supervision. 2019 Third IEEE International Conference on Robotic Computing (IRC). [paper]     

2018

• Chang Su, Jie Tong, Yongjun Zhu, Peng Cui, Fei Wang (2018). Network embedding in biomedical data science, Briefings in Bioinformatics, https://doi.org/10.1093/bib/bby117. [pdf]

• Xi Zhang, Dandi Chen, Yongjun Zhu, Chao Che, Chang Su, Sendong Zhao, Xu Min, Fei Wang (2018). A Multi-View Ensemble Classification Model for Clinically Actionable Genetic Mutations, NIPS'17 Competition: Building Intelligent Systems. [pdf]

• Chang Su, Xiaohong Guan, Youtian Du, Qian Wang, Fei Wang (2018). A fast multi-level algorithm for community detection in directed online social networks. Journal of Information Science. 44.3 (2018): 392-407. [pdf]

• Chang Su, Xiaohong Guan, Youtian Du, Xin Huang, Minhua Zhang (2018). Toward capturing heterogeneity for inferring diffusion networks: A mixed diffusion pattern model. Knowledge-Based Systems. 147 (2018): 81-93. [pdf]

Before 2017

• Jie Tong, Ying Qi, Xiangmiao Wang, Liyin Yu, Chang Su, Wenjun Xie, Jianbao Zhang (2017). Cell micropatterning reveals the modulatory effect of cell shape on proliferation through intracellular calcium transients. Biochimica et Biophysica Acta (BBA)-Molecular Cell Research. 1864.12 (2017): 2389-2401.

• Chang Su, Youtian Du, Xiaohong Guan, Chenhe Wu (2013). Maximizing topic propagation driven by multiple user nodes in micro-blogging. 38th Annual IEEE Conference on Local Computer Networks. pp. 751-754. [pdf]

• Youtian Du, Chang Su, Zhongmin Cai, Xiaohong Guan (2013). Web page and image semi-supervised classification with heterogeneous information fusion. Journal of Information Science 39.3 (2013): 289-306.

• Chenhe Wu, Youtian Du, Chang Su (2013). Topic recommendation method with finite driving user nodes in micro-blogging. Computer Engineering and Applications. 15 (2013): 33.