J11
|
High-Throughput Target Trial Emulation for Alzheimer’s Disease Drug Repurposing with Real-World Data
Chengxi Zang, Hao Zhang, Jie Xu, Hansi Zhang, Sajjad Fouladvand, Shreyas Havaldar, Feixiong Cheng, Kun Chen, Yong Chen, Benjamin Glicksberg, Jin Chen, and Jiang Bian, Fei Wang
Nature Communications (Accept, in print).
|
[PDF]
|
J10 |
Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records
Jie Xu, Fei Wang, Chengxi Zang, Hao Zhang, Kellyann Niotis, Ava L. Liberman, Cynthia M. Stonnington, Makoto Ishii, Prakash Adekkanattu, Yuan Luo, Chengsheng Mao, Luke V. Rasmussen, Zhenxing Xu, Pascal Brandt, Jennifer A. Pacheco, Yifan Peng, Guoqian Jiang, Richard Isaacson & Jyotishman Pathak
Scientific reports (2023).
|
[PDF]
|
J9
|
Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative
Chengxi Zang, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Edward J. Schenck, Dhruv Khullar, Anna S. Nordvig, Elizabeth A. Shenkman, Russell L. Rothman, Jason P. Block, Kristin Lyman, Mark G. Weiner, Thomas W. Carton, Fei Wang, Rainu Kaushal
Nature Communications (2023).
|
[PDF]
|
J8 |
Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes
Hao Zhang, Chengxi Zang, Zhenxing Xu, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Dhruv Khullar, Yiye Zhang, Anna Nordvig, Edward Schenck, Elizabeth Shenkman, Russel Rothman, Jason Block, Kristin Lyman, Mark Weiner, Thomas Carton, Fei Wang, Rainu Kaushal
Nature Medicine (2023).
|
[PDF]
|
J7 |
Racial/Ethnic Disparities in Post-acute Sequelae of SARS-CoV-2 Infection in New York: an EHR-Based Cohort Study from the RECOVER Program
Dhruv Khullar, Yongkang Zhang, Chengxi Zang, Zhenxing Xu, Fei Wang, Mark G. Weiner, Thomas W. Carton, Russell L. Rothman, Jason P. Block, Rainu Kaushal
Journal of General Internal Medicine (2023).
|
[PDF]
|
J6 |
Identifying environmental risk factors for post-acute sequelae of SARS-CoV-2 infection: An EHR-based cohort study from the recover program
Yongkang Zhang, Hui Hu, Vasilios Fokaidis, Colby Lewis V, Jie Xu, Chengxi Zang, Zhenxing Xu, Fei Wang, Michael Koropsak, Jiang Bian, Jaclyn Hall, Russell L. Rothman, Elizabeth A. Shenkman, Wei-Qi Wei, Mark G. Weiner, Thomas W. Carton, Rainu Kaushal
Environmental Advances (2023).
|
[PDF]
|
J5 |
Building the ModelChallenges and Considerations of Developing and Implementing Machine Learning Tools for Clinical Laboratory Medicine Practice
Yang, He S., Daniel D. Rhoads, Jorge Sepulveda, Chengxi Zang, Amy Chadburn, and Fei Wang.
Archives of Pathology & Laboratory Medicine (2022).
|
[PDF]
|
J4 |
Development of a screening algorithm for borderline personality disorder using electronic health records
Chengxi Zang, Marianne Goodman, Zheng Zhu, Lulu Yang, Ziwei Yin, Zsuzsanna Tamas, Vikas Mohan Sharma, Fei Wang, and Nan Shao
Scientific reports 12, no. 1 (2022): 1-12.
|
[PDF]
|
J3 |
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients
Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Jing Zhang,Riccardo Miotto, Zhangyang Wang, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
Cell Patterns, 2021.
|
[PDF]
|
J2 |
Exploring the collective human behavior in cascading systems: a comprehensive framework
Yunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui, Chaoming Song & Wenwu Zhu.
Knowledge and Information Systems (KAIS), 2020.
|
[PDF]
|
J1 |
On Power Law Growth of Social Networks.
Chengxi Zang, Peng Cui, Christos Faloutsos, Wenwu Zhu.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
|
[PDF]
[Code]
|