Wang Lab
Weill Cornell Medicine
Selected Publications
(Full publications please see my Google Scholar page)2023
- Hao Zhang, Chengxi Zang, Zhenxing Xu, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Dhruv Khullar,
Yiye Zhang, Anna S Nordvig, Edward J Schenck, Elizabeth A Shenkman, Russell L Rothman, Jason P Block, Kristin Lyman, Mark G Weiner,
Thomas W Carton, Fei Wang*, Rainu Kaushal. (* Corresponding Author)
Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.
Nature Medicine. 29, pages 226–235 (2023).
Impact Factor: 87.241
[Link] [news] [news] [news] [news] [news] - 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. (* Corresponding Author)
Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative.
Nature Communications. 14, Article number: 1948 (2023).
Impact Factor: 17.694
[Link] [news] - 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. Volume 26, Issue 4, 21 April 2023, 106460
[Link] [video] - Qian Yang, Yuexing Hao, Kexin Quan, Stephen Yang, Yiran Zhao, Volodymyr Kuleshov, Fei Wang
Harnessing Biomedical Literature to Calibrate Clinicians’ Trust in AI Decision Support Systems.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI).
[Link] [Research Gate] [news] - Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, Volodymyr Kuleshov
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models.
Proceedings of the The Fortieth International Conference on Machine Learning (ICML).
Acceptance Rate: 1,827/6,358=29.19%
[Link]
2022
- Jie Xu, Yunyu Xiao, Wendy Hui Wang, Yue Ning, Elizabeth A. Shenkman, Jiang Bian, Fei Wang.
Algorithmic fairness in computational medicine..
eBioMedicine. Volume 84, October 2022.
Impact Factor: 11.2
[Link] [medRxiv] - Xu, Zhenxing, 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..
Critical Care. 26, Article number: 197. 2022.
Impact Factor: 19.33. Highlighted in AMIA 2022 Year-in-Review Session.
[Link] - Adrienne Kline, Hanyin Wang, Yikuan Li, Saya Dennis, Meghan Hutch, Zhenxing Xu, Fei Wang, Feixiong Cheng, Yuan Luo.
Multimodal Machine Learning in Precision Health: A Scoping Review.
npj Digital Medicine 5, Article Number: 1. 2022.
Impact Factor: 13.49.
[Link] [medRxiv] [news] - Xiangxiang Zeng, Fei Wang, Yuan Luo, Seung-gu Kang, Jian Tang, Felice C Lightstone, Evandro F Fang,
Wendy Cornell, Ruth Nussinov, Feixiong Cheng
Deep Generative Molecular Design Reshapes Drug Discovery.
Cell Reports Medicine. 2022.
Impact Factor: 16.998
[Link] - Yi Guo, Qian Li, Xi Yang, Michael S. Jaffee, Yonghui Wu, Fei Wang and Jiang Bian.
Prevalence of Alzheimer's and related dementia diseases and risk factors among transgender adults, Florida, 2012 - 2020.
The American Journal of Public Health. 112(5):754-757. 2022.
Impact Factor: 11.58
[Link] - Wanwan Xu, Chang Su, Yan Li, Steven Rogers, Fei Wang, Kun Chen, Robert Aseltine.
Improving Suicide Risk Prediction via Targeted Data Fusion: Proof of Concept Using Medical Claims Data.
Journal of American Medical Informatics Association (JAMIA). Volume 29, Issue 3, March 2022, Pages 500–511.
[Link] [Editorial] - Yingsong Huang, Bing Bai, Shengwei Zhao, Kun Bai, Fei Wang.
Uncertainty-aware Learning Against Label Noise on Imbalanced Datasets.
AAAI Conference on Artificial Intelligence (AAAI). 2022.
Acceptance Rate: 1349/9251=14.58%
[Link] - Chunyu Wei, Bing Bai, Kun Bai, Fei Wang.
GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction.
The ACM Web Conference (WWW). Pages 2120–2130. 2022.
Acceptance Rate: 323/1822=17.7%
[Link] - Sen Cui, Jian Liang, Weishen Pan, Kun Chen, Changshui Zhang, Fei Wang.
Collaboration Equilibrium in Federated Learning.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Pages 241–251. 2022.
Acceptance Rate: 254/1695=14.99%
[Link] [ArXiv] [Code] - Shunyu Wei, Jian Liang, Di Liu, and Fei Wang.
Contrastive Graph Structure Learning via Information Bottleneck for Recommendation.
Advances in Neural Information Processing Systems (NeurIPS). 2022.
Acceptance Rate: 25.6%
[Link]
2021
- Fei Wang.
Machine Learning for Predicting Rare Clinical Outcomes—Finding Needles in a Haystack.
JAMA Network Open. 4.5 Pages: e2110738-e2110738. 2021.
Impact Factor: 8.483
[Link] [MedPage Today] - Faten A Sayed, Lay Kodama, Joe C Udeochu, Li Fan, Gillian K Carling,
David Le, Qingyun Li, Lu Zhou, Hansruedi Mathys, Minghui Wang, Xiang Niu, Linas Mazutis, Xueqiao Jiang,
Xueting Wang, Man Ying Wong, Fuying Gao, Maria Telpoukhovskaia, Tara E Tracy, Georgia Frost, Yungui Zhou,
Yaqiao Li, Matthew Brendel, Yue Qiu, Zuolin Cheng, Guoqiang Yu, John Hardy, Giovanni Coppola, Shiaoching Gong,
Fei Wang, Michael A DeTure, Bin Zhang, Lei Xie, Dennis W Dickson, Wenjie Luo, and Li Gan.
AD-linked R47H-TREM2 Mutation Induces Disease-Enhancing Proinflammatory Microglial States in Mice and Humans.
Science Translational Medicine. Vol 13, Issue 622. Dec. 2021.
Impact Factor: 17.96
[Link] - Jie Xu, Wei Zhang, Fei Wang.
A(DP)^2SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). To Appear. 2021.
Impact Factor: 16.39
[Link] [ArXiv] - Jingyuan Wang, Ke Tang, Kai Feng, Xin Lin, Weifeng Lv, Kun Chen, Fei Wang.
Impact of Temperature and Relative Humidity on the Transmission of COVID-19: A Modeling Study in China and the United States.
BMJ Open. 11, no. 2. Pages: e043863. 2021.
Cited by more than 600 times.
[Link] - Yuantong Li, Fei Wang, Mengying Yan, Edward Cantu, Fan Nils Yang, Hengyi Rao, and Rui Feng.
Peel Learning for Pathway-Related Outcome Prediction.
Bioinformatics. btab402. 2021.
[Link] - Chang Su, Yongkang Zhang, James H Flory, Mark G Weiner, Rainu Kaushal, Edward J Schenck, Fei Wang.
Novel Clinical Subphenotypes in COVID-19: Derivation, Validation, Prediction, Temporal Patterns, and Interaction with Social Determinants of Health.
npj Digital Medicine 4, Article Number: 110. 2021.
Impact Factor: 11.653. Highlighted in AMIA 2022 Year-in-Review Session.
[Link] [medRxiv] [news] - Zhaoyi Chen, Hansi Zhang, Yi Guo, Thomas J George, Mattia Prosperi, William R Hogan, Zhe He, Elizabeth A Shenkman, Fei Wang, Jiang Bian.
Exploring the Feasibility of Using Real-World Data from a Large Clinical Data Research Network to Simulate Clinical Trials of Alzheimer’s Disease.
npj Digital Medicine. 4, Article number: 84. 2021.
Impact Factor: 11.653
[Link] [Editorial] - 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 To Appear. 2021.
Impact Factor: 7.923
[Link] - Akhil Vaid, Suraj K Jaladanki, Jie Xu, Shelly Teng, Arvind Kumar, Samuel Lee, Sulaiman Somani, Ishan Paranjpe,
Jessica K De Freitas, Tingyi Wanyan, Kipp W Johnson, Mesude Bicak, Eyal Klang, Young Joon Kwon, Anthony Costa, Shan Zhao, Riccardo Miotto,
Alexander W Charney, Erwin Böttinger, Zahi A Fayad, Girish N Nadkarni, Fei Wang, Benjamin S Glicksberg.
Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19.
JMIR medical informatics. 9(1) Pages: e24207. 2021.
[Link] [News Medical] - Sendong Zhao, Chang Su, Zhiyong Lu, Fei Wang.
Recent Advances in Biomedical Literature Mining.
Briefings in Bioinformatics. 22, no. 3. Pages: bbaa057. 2021.
Impact Factor: 11.62
[Link] - Yi Guo, Yahan Zhang, Tianchen Lyu, Mattia Prosperi, Fei Wang, Hua Xu, and Jiang Bian.
The Application of Artificial Intelligence and Data Integration in COVID-19 Studies: A Scoping Review.
Journal of American Medical Informatics Association (JAMIA). Volume 28, Issue 9, September 2021, Pages 2050–2067.
[Link] - Yufang Huang, Yifan Liu, Peter A D Steel, Kelly M. Axsom, John R. Lee, Sri Lekha Tummalapalli, Fei Wang,
Jyotishman Pathak, Lakshminarayanan Subramanian, Yiye Zhang.
Deep Significance Clustering: A Novel Approach for Identifying Risk-Stratified and Predictive Patient Subgroups.
Journal of American Medical Informatics Association (JAMIA). Volume 28, Issue 12, December 2021, Pages 2641–2653.
[Link] - Sen Cui, Weishen Pan, Changshui Zhang, Fei Wang.
Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 207-217. 2021.
Acceptance Rate: 238/1541=15.44%
[Link] [ArXiv] [Code] - Weishen Pan, Sen Cui, Jiang Bian, Changshui Zhang, Fei Wang.
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 1287-1297. 2021.
Acceptance Rate: 238/1541=15.44%. Highlighted in AMIA 2021 Year-in-Review Session.
[Link] [ArXiv] [Code] - Zhengze Zhou, Giles Hooker, Fei Wang.
S-LIME: Stabilized-LIME for Model Explanation.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 2429–2438. 2021.
Acceptance Rate: 238/1541=15.44%
[Link] [ArXiv] - Zhou Liu, Yanxuan Li, Xingzhi Sun, Fei Wang, Gang Hu, Guotong Xie.
Dialogue Based Disease Screening Through Domain Customized Reinforcement Learning.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 1120–1128. 2021.
Acceptance Rate: 238/1541=15.44%
[Link] - Bing Bai, Jian Liang, Guanhua Zhang, Hao Li, Kun Bai, Fei Wang.
Why Attentions May Not Be Interpretable?
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 25–34. 2021.
Acceptance Rate: 238/1541=15.44%
[Link] [ArXiv] - Jian Tang, Fei Wang and Feixiong Cheng.
Artificial Intelligence for Drug Discovery.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). 4074-4075. 2021.
[Link] [Tutorial] - Sen Cui, Weishen Pan, Jian Liang, Changshui Zhang, and Fei Wang.
Fair and Consistent Federated Learning.
Advances in Neural Information Processing Systems (NeurIPS). 2021.
Acceptance Rate: 26%
[Link] - Yi He, Jiaxian Dong, Bo-Jian Hou, Yu Wang and Fei Wang.
Online Learning in Variable Feature Spaces with Mixed Data.
IEEE International Conference on Data Mining (ICDM). 2021.
Regular Paper. Acceptance Rate: 98/990=9.9%
[Link] - Chengxi Zang and Fei Wang.
SCEHR: Supervised Contrastive Learning for Clinical Risk Predictions with Electronic Health Records.
IEEE International Conference on Data Mining (ICDM). 2021.
Regular Paper. Acceptance Rate: 98/990=9.9%
[Link] - Xiao Xu, Xian Xu, Yuyao Sun, Xiaoshuang Liu, Xiang Li, Guotong Xie and Fei Wang.
Predictive Modeling of Clinical Events with Mutual Enhancement Between Longitudinal Patient Records and Medical Knowledge Graph.
IEEE International Conference on Data Mining (ICDM). 2021.
Regular Paper. Acceptance Rate: 98/990=9.9%
[Link]
2020
- He S. Yang, Yu Hou, Ljiljana V. Vasovic, Peter Steel, Amy Chadburn, Sabrina E. Racine-Brzostek, Priya Velu,
Melissa M Cushing, Massimo Loda, Rainu Kaushal, Zhen Zhao, Fei Wang.
Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.
Clinical Chemistry. Volume 66, Issue 11, Page: 1396–1404. 2020.
Impact Factor: 8.327
[Link] [medRXiv] [Editorial] [Follow-Up] [Modern Healthcare] [Dark Daily] [Weill Cornell Newsroom] [AACC] - Fei Wang, Rainu Kaushal, Dhruv Khullar.
Should Health Care Demand Interpretable Artificial Intelligence or Accept “Black Box” Medicine?
Annals of Internal Medicine. Volume 172, Issue 1. Page: 59-60. 2020.
Impact Factor: 25.39
[Link] [Faculty Opinions] - Yadi Zhou, Fei Wang, Jian Tang, Ruth Nussinov, and Feixiong Cheng.
Artificial Intelligence in COVID-19 Drug Repurposing.
The Lancet Digital Health. Volume 2, Issue 12, E667-E676, December 01, 2020.
Impact Factor: 24.519
[Link] [Cover] - Jian Liang, Ziqi Liu, Jiayu Zhou, Xiaoqian Jiang, Changshui Zhang, Fei Wang.
Model-Protected Multi-Task Learning.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). To Appear. 2020.
Impact Factor: 16.39
[Link] [ArXiv] - Sendong Zhao, Meng Jiang, Bing Qin, Ting Liu, Chengxiang Zhai, Fei Wang.
Structural and Textual Information Fusion for Symptom and Disease Representation Learning.
IEEE Transactions on Knowledge and Data Engineering (TKDE). To Appear. 2020.
[Link] - Mengying Sun, Sendong Zhao, Coryandar Gilvary, Olivier Elemento, Jiayu Zhou, Fei Wang.
Graph Convolutional Networks for Computational Drug Development and Discovery.
Briefings in Bioinformatics 21, no. 3. 2020. Pages 919-935.
Impact Factor: 11.62
[Link] - Chang Su, Zhenxing Xu, Jyotishman Pathak, Fei Wang.
Deep learning in Mental Health Outcome Research: a Scoping Review.
Translational Psychiatry 10, no. 1. 2020. Pages 1-26.
[Link] - Chang Su, Robert Aseltine, Riddhi Doshi, Kun Chen, Steven Rogers, Fei Wang.
Machine Learning for Suicide Risk Prediction in Children and Adolescents with Electronic Health Records.
Translational Psychiatry. 2020. 10, Article number: 413.
[Link] - Fengyi Tang, Ikechukwu Uchendu, Fei Wang, Hiroko H. Dodge, and Jiayu Zhou.
Scalable Diagnostic Screening of Mild Cognitive Impairment Using AI Dialogue Agent.
Scientific Reports 10, no. 1. 2020. 1-11.
Highlighted in AMIA 2020 Year-in-Review Session.
[Link] - Riddhi P. Doshi, Kun Chen, Fei Wang, Harold Schwartz, Alfred Herzog, Robert H. Aseltine.
Identifying Risk Factors for Mortality Among Patients Previously Hospitalized for a Suicide Attempt.
Scientific Reports 10, no. 1. 2020. 1-9.
[Link] - Chengxi Zang, Fei Wang.
MoFlow: An Invertible Flow Model for Generating Molecular Graphs.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Pages 617–626. 2020.
Acceptance Rate: 216/1279=16.89%
[Link] [ArXiv] [Code] - Chengxi Zang, Fei Wang.
Neural Dynamics on Complex Networks.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Pages 892–902. 2020.
Acceptance Rate: 216/1279=16.89%
[Link] [ArXiv] [DLGMA'20 Best Paper Award] - Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang.
Adversarial Infidelity Learning for Model Interpretation.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Pages 286–296. 2020.
Acceptance Rate: 216/1279=16.89%
[Link] [ArXiv] - Junqi Zhang, Bing Bai, Ye Lin, Jian Liang, Kun Bai, Fei Wang.
General-Purpose User Embeddings based on Mobile App Usage.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Pages 2831–2840. 2020.
Acceptance Rate: 216/1279=16.89%
[Link] [ArXiv] - Fei Wang, Peng Cui, Jian Pei, Yangqiu Song, Chengxi Zang.
Recent Advances on Graph Analytics and Its Applications in Healthcare.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Pages 3545–3546. 2020.
[Link] [Tutorial Website] - Xu, Jie, Zhenxing Xu, Peter Walker, Fei Wang.
Federated Patient Hashing.
AAAI Conference on Artificial Intelligence (AAAI). Pages 6486-6493. 2020.
Acceptance Rate: 1591/8800=18.08%
[Link] - Jie Xu, Zhengxing Xu, Bin Yu, Fei Wang.
Order-Preserving Metric Learning for Mining Multivariate Time Series.
IEEE International Conference on Data Mining (ICDM). 2020.
Acceptance Rate: 91/930=9.78%
[Link] - Sendong Zhao, Yong Huang, Chang Su, Yuantong Li, Fei Wang.
Interactive Attention Networks for Semantic Text Matching.
IEEE International Conference on Data Mining (ICDM). 2020.
Acceptance Rate: 91/930=9.78%
[Link] - Fengyi Tang, Lifan Zeng, Fei Wang, Jiayu Zhou.
Adversarial Precision Sensing with Healthcare Applications.
IEEE International Conference on Data Mining (ICDM). 2020.
Acceptance Rate: 91/930=9.78%
[Link]