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Liwei Wang, PhD joined McWilliams School of Biomedical Informatics as an associate professor of the Center for Translational AI Excellence and Applications in Medicine (TEAM-AI) in June 2023. With a diverse background in informatics, medicine, pharmacology and public health, Dr. Wang has a strong focus on translating informatics solutions for cancer, precision medicine, mental health, and pharmacogenomics.

Throughout her career, Dr. Wang has engaged in extensive collaborations with clinicians, epidemiologists, and statisticians. She has served as a co-investigator and key investigator for multiple research grants from the National Library of Medicine (NLM) and the National Cancer Institute (NCI). Her involvement in these projects has allowed her to lead informatics initiatives and develop valuable resources, including lexicon, ontology and natural language processing algorithms, which have been successfully applied for large-scale information extraction and data mining. She utilizes various real-world data sources, such as Electronic Health Records (EHRs), FDA Adverse Event Reporting System (FAERS), to generate evidence, facilitating research excellence and practical applications.

  • Tell us about your research center and/or what research you are currently working on?
    The Center for Translational AI Excellence and Applications in Medicine (TEAM-AI) focuses on advancing translational sciences in data science, informatics, and artificial intelligence for medicine and healthcare, and aims to accelerate the digital transformation of medicine and healthcare through methodology innovation and team science collaboration.

    My current work focuses on developing cohort identification and computational phenotyping algorithms, as well as resources and tools for generating real-world evidence by leveraging AI and informatics methodologies. This work aims to facilitate knowledge discovery, translation and implementation of AI techniques.
  • What type of student or Postdoctoral Fellow are you looking for to work in your center?
    Students who are self-motivated, and with background of AI, data science, and informatics techniques.
  • What does the future of your research look like?
    I envision that my research will empower clinical research, facilitate the translation of AI into practice, and ultimately improve patients’ quality of life.
  • What does the future of informatics look like?
    Informatics will draw more attention and play an indispensable role in health care within the context of an information society, not only in the medical domain. More relevant disciplines and experts will embrace informatics for collaboration and advancements in clinical excellence.


  • PhD, Medical Informatics, Jilin University, 2014
  • MS, Library Science, Jilin University, 2006
  • MD, Norman Bethune University of Medical Sciences, 1999

Areas of Expertise

  • Information extraction and data mining
  • Cancer informatics
  • Mental health informatics
  • Real-world evidence generation
  • Biomedical lexicon, ontology, and semantics
  • Computational phenotyping algorithms
  • Adverse drug event surveillance

Staff Support

Blanca Torres | 713-486-0114

Selected Publications

  1. Wang, Liwei, Huan He, Andrew Wen, Sungrim Moon, Sunyang Fu, Kevin J. Peterson, Xuguang Ai, Sijia Liu, Ramakanth Kavuluru, and Hongfang Liu. "Acquisition of a Lexicon for Family History Information: Bidirectional Encoder Representations From Transformers–Assisted Sublanguage Analysis." JMIR Medical Informatics 11 (2023): e48072.
  2. Wang, Liwei, Sunyang Fu, Andrew Wen, Xiaoyang Ruan, Huan He, Sijia Liu, Sungrim Moon et al. "Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing." JCO Clinical Cancer Informatics 6 (2022): e2200006.
  3. Zhou, Sicheng, Nan Wang, Liwei Wang, Hongfang Liu, and Rui Zhang. "CancerBERT: a cancer domain-specific language model for extracting breast cancer phenotypes from electronic health records." Journal of the American Medical Informatics Association 29, no. 7 (2022): 1208-1216.
  4. Wen, Andrew, Liwei Wang, Huan He, Sijia Liu, Sunyang Fu, Sunghwan Sohn, Jacob A. Kugel et al. "An aberration detection-based approach for sentinel syndromic surveillance of COVID-19 and other novel influenza-like illnesses." Journal of biomedical informatics 113 (2021): 103660.
  5. Wang, Liwei, Janet E. Olson, Suzette J. Bielinski, Jennifer L. St. Sauver, Sunyang Fu, Huan He, Mine S. Cicek, Matthew A. Hathcock, James R. Cerhan, and Hongfang Liu. "Impact of diverse data sources on computational phenotyping." Frontiers in genetics 11 (2020): 556.
  6. Kronzer, Vanessa L., Liwei Wang, Hongfang Liu, John M. Davis III, Jeffrey A. Sparks, and Cynthia S. Crowson. "Investigating the impact of disease and health record duration on the eMERGE algorithm for rheumatoid arthritis." Journal of the American Medical Informatics Association 27, no. 4 (2020): 601-605.
  7. Wang, Liwei, Lei Luo, Yanshan Wang, Jason Wampfler, Ping Yang, and Hongfang Liu. "Natural language processing for populating lung cancer clinical research data." BMC medical informatics and decision making 19 (2019): 1-10.
  8. Wang, Liwei, Yanshan Wang, Feichen Shen, Majid Rastegar-Mojarad, and Hongfang Liu. "Discovering associations between problem list and practice setting." BMC medical informatics and decision making 19, no. 3 (2019): 13-22.
  9. Wang, Liwei, Jason Wampfler, Angela Dispenzieri, Hua Xu, Ping Yang, and Hongfang Liu. "Achievability to extract specific date information for cancer research." In AMIA Annual Symposium Proceedings, vol. 2019, p. 893. American Medical Informatics Association, 2019.
  10. Fan, Yadan, Andrew Wen, Feichen Shen, Sunghwan Sohn, Hongfang Liu, and Liwei Wang*. "Evaluating the impact of dictionary updates on automatic annotations based on clinical NLP systems." AMIA Summits on Translational Science Proceedings 2019 (2019): 714.
  11. Wang, Liwei, Majid Rastegar-Mojarad, Zhiliang Ji, Sijia Liu, Ke Liu, Sungrim Moon, Feichen Shen et al. "Detecting pharmacovigilance signals combining electronic medical records with spontaneous reports: a case study of conventional disease-modifying antirheumatic drugs for rheumatoid arthritis." Frontiers in pharmacology 9 (2018): 875.
  12. Wang, Yanshan, Liwei Wang, Majid Rastegar-Mojarad, Sungrim Moon, Feichen Shen, Naveed Afzal, Sijia Liu et al. "Clinical information extraction applications: a literature review." Journal of biomedical informatics 77 (2018): 34-49.
  13. Wang, Liwei, Mei Li, Yuying Cao, Zhengqi Han, Xueju Wang, Elizabeth J. Atkinson, Hongfang Liu, and Shreyasee Amin. "Proton pump inhibitors and the risk for fracture at specific sites: data mining of the FDA adverse event reporting system." Scientific reports 7, no. 1 (2017): 5527.
  14. Wang, Liwei, Mei Li, Jiangan Xie, Yuying Cao, Hongfang Liu, and Yongqun He. "Ontology-based systematical representation and drug class effect analysis of package insert-reported adverse events associated with cardiovascular drugs used in China." Scientific reports 7, no. 1 (2017): 13819.
  15. Wang, Yanshan, Liwei Wang, Majid Rastegar-Mojarad, Sijia Liu, Feichen Shen, and Hongfang Liu. "Systematic analysis of free-text family history in electronic health record." AMIA Summits on Translational Science Proceedings 2017 (2017): 104.
  16. Rastegar-Mojarad, Majid, Sunghwan Sohn, Liwei Wang, Feichen Shen, Troy C. Bleeker, William A. Cliby, and Hongfang Liu. "Need of informatics in designing interoperable clinical registries." International journal of medical informatics 108 (2017): 78-84.
  17. Wang, Liwei, Xiaoyang Ruan, Ping Yang, and Hongfang Liu. "Comparison of three information sources for smoking information in electronic health records." Cancer informatics 15 (2016): CIN-S40604.
  18. Wang, Liwei, Hongfang Liu, Christopher G. Chute, and Qian Zhu. "Cancer based pharmacogenomics network supported with scientific evidences: from the view of drug repurposing." BioData mining 8, no. 1 (2015): 1-14.
  19. Wang, Liwei, Guoqian Jiang, Dingcheng Li, and Hongfang Liu. "Standardizing adverse drug event reporting data." Journal of biomedical semantics 5, no. 1 (2014): 1-13.
  20. Jiang, Guoqian, Liwei Wang, Hongfang Liu, Harold R. Solbrig, and Christopher G. Chute. "Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic web technologies." In MEDINFO 2013, pp. 496-500. IOS Press, 2013.