Rui Zhang, PhD, MS

Assistant Professor, Department of Pharmaceutical Care & Health Systems

Rui Zhang

Contact Info

zhan1386@umn.edu

Office Phone 612-626-4209

Office Address:
8-116 Phillips-Wangensteen Building

Mailing Address:
MMC 912
420 Delaware St SE
Minneapolis, MN 55455

PhD, University of Minnesota, (Health Informatics), 2013

MS, University of Iowa, (Chemistry), 2008; University of Iowa, (Informatics), 2010

Summary

Dr. Zhang was jointly hired as an Assistant Professor in the Department of Pharmaceutical Care & Health System (PCHS) and the Institute for Health Informatics (IHI). He obtained his PhD degree in Health Informatics from University of Minnesota and a master’s degree in both Informatics and Chemistry from University of Iowa. 

Dr. Zhang has extensive education background and research experience in the field of health and biomedical informatics, especially biomedical natural language processing and text mining. His research interests include the secondly analysis of electronic health record (EHR) data for patient care as well as pharmacovigilance knowledge discovery through mining a large scale of biomedical literature.

Dr. Zhang has published over 30 peer-review publications and is the Principal Investigator on a NIH R01 research award entitled “An Informatics Framework for Discovery and Ascertainment of Drug-Supplement Interactions” (2017-2021). 

He is also the recipient of UMN grant-in-aid award and UMII on the horizon grant. His work has been recognized on a national and international scale including Journal of Biomedical Informatics (JBI) Editor’s Choice (2014), a nomination for Marco Ramoni Distinguished Paper Award for Translational Bioinformatics (2015), and best student papers in American Medical Informatics Association (AMIA) Annual Symposium (2011), MEDINFO (2013), and AMIA Joint Summits (2014). 

In additional, his work on mining 23 million biomedical publications to discover drug-supplement interactions has been highlighted by The Wall Street Journal and Fox News.

Awards & Recognition

  • 2016 - Best Poster Award in BHI-2016 IEEE International Conference on Biomedical and Health Informatics
  • 2015 - Nominated as Marco Ramoni Distinguished Paper Award for Translational Bioinformatics
  • 2014 - Manuscript selected as Student Paper Competition Finalist in AMIA Joint Summits
  • 2013-14 - Health Information and Management Systems Society Scholarship (HIMSS), Minnesota Chapter
  • 2013 - Manuscript selected as Student Paper Competition Finalist in MEDINFO2013 (international, IMIA)
  • 2012-13 - Doctoral Dissertation Fellowship (All-University Competition), University of Minnesota
  • 2011, 2013 - Fellow, International Partnership in Health Informatics Education (IPHIE) Master Class

Research

Research Summary/Interests

  • Natural Language Processing
  • Text Mining
  • Literature-based Discovery
  • Translational Informatics
  • Statistic Analysis
  • Machine Learning

Research Funding Grants

An Informatics Framework for Discovery and Ascertainment of Drug-Supplement Interactions Role: Principal Investigator Funding Agency: NIH/NCCIH 1 R01 AT009457 (PI: Zhang) Project Dates: 04/2017–03/2021

Discovery and Visualization of New Information from Clinical Reports Role: Co-Investigator Funding Agency: AHRQ 1 R01 HS022085-01 (Melton-Meaux) Project Dates: 09/01/2013–08/30/2017 This grant develops and evaluates visualization methods by “highlighting” important information from clinical texts, improving user interface design for clinical texts, and conducts a prospective clinical trial with a tool in the EHR to highlight new, non-redundant information in clinical documents.

Using Electronic Health Records to Validate Literature Discovery-Based Drug-Drug Interactions Role: Principal Investigator Funding Agency: University of Minnesota Office of the Vice President for Research Grant-in-Aid Project Dates: 01/2016–06/2017

Improving Breast Cancer Survivors’ Disease Management Outcomes through Smartphone Apps and Online Health Community Role: Co-Investigator Funding Agency: University of Minnesota Office of the Vice President for Research Grant-in-Aid (PI: Gao) Project Dates: 07/2016–01/2018

Large-scale discovery of drug-supplements interactions in biomedical literature Role: Principal Investigator Funding Agency: University of Minnesota Informatics Institute On the Horizon Grant Project Dates: 07/2014–07/2015

Publications

  1. Breitenstein M, Liu H, Maxwell K, Pathak J, Zhang R. Electronic health record phenotypes for precision medicine: perspectives and caveats from treatment of breast cancer at a single institution. Clinical and Translational Science. 2017. 
  2. Jian Z, Guo X, Lou S, Ma H, Zhang S, Zhang R, Lei J. A Cascaded Approach for Chinese Clinical Text De-Identification with Less Annotation Effort. Journal of Biomedical Informatics, 2017; 73: 76-83.
  3. Zhang R, Simon G, Yu F. Advancing Alzheimer's Research: A Review of Big Data Promises. International Journal of Medical Informatics. 2017;106:48-56.
  4. Sun D, Simon G, Skube S, Blaes A, Melton GB, Zhang R, Causal Phenotyping for Susceptibility to Cardiotoxicity from Antineoplastic Breast Cancer Medications. Proceedings of the American Medical Informatics Association Symposium. 2017.
  5. Zhang R, Pakhomov S, Arsoniadis E, Lee T, Wang Y, Melton G. Detecting clinically relevant new information in clinical notes across specialties and settings, BMC Medical Informatics and Decision Making, 2017 (17) Sp 2:68.
  6. Fan Y*, Adam T, McEwan R, Pakhomov S, Melton G, Zhang R. Detecting Signals of Interactions between Warfarin and Supplements in Electronic Health Records. Stud Health Techno Inform 2017.
  7. Wang Y*, Gunashekar R, Adam T, Zhang R. Mining Adverse Events of Dietary Supplements from Product Labels by Topic Modeling. Stud Health Techno Inform 2017.
  8. Sun D*, Sarda G, Skube S, Blaes A, Khairat S, Melton G, Zhang R. Phenotyping and Visualizing Infustion-related Reactions for Breast Cancer Patients. Stud Health Techno Inform 2017.
  9. Fan Y*, He L, Pakhomov S, Melton GB, Zhang R. Classifying Supplement Use Status in Clinical Notes. Proceedings of the American Medical Informatics Association Symposium Joint Summit on Translational Science 2017. (Student Paper Competition Finalist)
  10. Fan Y*, He L, Zhang R. Classification of Status for Supplement Use in Clinical Notes. Proceedings of the IEEE International conference on Bioinformatics and Biomedicine. 2016: 1054-61.
  11. Marc D*, Beattie J, Herasevich, V, Gatewood, L, Zhang R. Assessing Metadata Quality of a Federally Sponsored Health Data Repository. Proceedings of the American Medical Informatics Association Symposium. 2016; 2016: 864–73.
  12. Wang Y*, Adam TJ, Zhang R. Term Coverage of Dietary Supplements Ingredients in Product Labels. Proceedings of the American Medical Informatics Association Symposium. 2016: 2053-2061.
  13. Zhang R. Healthcare Data Analytics. Chandan K. Reddy and Charu C. Aggarwal. Boca Raton, FL: Chapman & Hall/CRC Press (2015) 724 pp. Journal of Biomedical Informatics. 2015;58:166-7.
  14. Zhang R, Manohar N, Arsoniadis E, Wang Y, Adam T, Pakhomov S, Melton GB. Evaluating Term Coverage of Herbal and Dietary Supplements in Electronic Health Records. Proceedings of the American Medical Informatics Association Symposium. 2015:1361-70.
  15. Manohar N*, Adam TJ, Pakhomov SV, Melton GB, Zhang R. Evaluation of Herbal and Dietary Supplement Resource Term Coverage. Stud Health Technol Inform 2015;216:785-9.
  16. Marc D*, Zhang R, Beattie J, Gatewood LC, Khairat S. Indexing Publicly Available Health Data with Medical Subject Headings (MeSH): An Evaluation of Term Coverage. Stud Health Technol Inform 2015;216:529-33.
  17. Zhang R, Adam T, Simon G, Cairelli M, Rindflesch T, Pakhomov S, Melton GB. Mining Biomedical Literature to Explore Interactions between Cancer Drugs and Dietary Supplements. AMIA Joint Summits on Translational Science. 2015:69-73. (Distinguished Paper Award Nominee).
  18. Zhang R, Pakhomov S, Janet T Lee Melton GB. Using language models to identify relevant new information in inpatient clinical note. Proceedings of the American Medical Informatics Association Symposium. 2014:1268-76.
  19. Zhang R, Cairelli M, Fiszman M, Kilicoglu H, Rindflesch TC, Pakhomov S, Melton GB. Exploiting Literature-derived knowledge and semantics to identify potential prostate cancer drugs. Cancer Informatics. 2014;13(S1):103-11.
  20. Zhang R, Cairelli M, Fiszman M, Graciela R, Kilicoglu H, Rindflesch TC, Pakhomov S, Melton GB. Using semantic predications to discover drug-drug interactions from biomedical literature. Journal of Biomedical Informatics. 2014;49:134-47. (Manuscript selected as JBI Editors' Choice)
  21. Zhang R, Pakhomov S, Janet T. Lee, Melton GB. Navigating longitudinal clinical notes with an automated method for detecting new information. Studies in Health Technology and Informatics. 2013;192: 754-8. (Manuscript selected as a Student Paper Competition Finalist)
  22. Zhang R, Pakhomov S, Gladding S, Aylward M, Borman-Shoap E, Melton GB. Automated assessment of medical training evaluation text. Proceedings of the American Medical Informatics Association Symposium. 2012: 1459-1468.
  23. Zhang R, Pakhomov S, Melton GB. Automated identification of relevant new information in clinical narrative. Proceedings of the 2nd ACM SIGHIT International Health Informatics (IHI?12) Symposium. 2012: 837-841.
  24. Farri O, Rahman A, Monsen KA, Zhang R, Pakhomov S, Pieczkiewicz DS, Speedie SM, Melton GB. Impact of a prototype visualization tool for new information in EHR clinical documents. Applied Clinical Informatics. 2012; 3(4): 404-418.
  25. Zhang R, Pakhomov S, McInnes TB, Melton GB. Evaluating measures of redundancy in clinical texts. Proceedings of the American Medical Informatics Association Symposium. 2011: 1612-1620. (Manuscript selected as a Student Paper Competition Finalist)
  26. Zhang R, Wang Y, Melton GB. "Natural Language Processing in Medicine." In Medical Applications of Artificial Intelligence, CRC Press, Taylor & Francis, Boca Raton, Florida, 2013, ISBN: 1439884331

Media

In The News

“Researchers at the University of Minnesota in Minneapolis are exploring interactions between cancer drugs and dietary supplements, based on data extracted from 23 million scientific publications, according to lead author Rui Zhang, a clinical assistant professor in health informatics. In a study published last year by a conference of the American Medical Informatics Association, he says, they identified some that were previously unknown.”
http://www.wsj.com/articles/what-you-should-know-a...