Stephane M. Meystre, MD, PhD, MS

Research Interests

  • Clinical Natural Language Processing
  • Clinical Decision Support Systems
  • Clinical Informatics
  • Clinical Research Informatics
  • Ontology
  • Machine Learning/ Artifical Intelligence
  • Telemedicine

Labs

Lab Website

Languages

  • English
  • French
  • German
  • Italian

Academic Information

  • Departments: Biomedical Informatics - Adjunct Assistant Professor

Board Certification

  • Swiss Federal Department of Home Affairs
  • Swiss Medical Association

Academic Office Information

  • Biomedical Informatics
    421 Wakara Way, Room: 140
    Salt Lake City, UT 84108

Academic Bio

Dr. Stephane M. Meystre earned his PhD in Medical Informatics from the University of Utah, his MD from the University of Lausanne, Switzerland, and his MS in Medical Informatics from the University of California, Davis. He is a Research Assistant Professor in the University of Utah’s Department of Biomedical Informatics.

His expertise in clinical informatics research involves the following areas: easing access to clinical data for clinical care and research purposes using advanced techniques such as Natural Language Processing (NLP) for information extraction and automated de-identification; providing research support by integrating clinical with research data; and integrating research with clinical systems. He also specializes in ontologies development automation, knowledge representation, and clinical text disambiguation. Other areas of interest include: biomedical information and knowledge modeling and representation; telemedicine, teleconsultation, and remote monitoring.

Prior to joining the department in 2007, Dr. Meystre was a project leader at the University Hospital of Lausanne (2005-2007), where he oversaw the conception of a new web portal to facilitate access to patient clinical data in a multiple legacy applications environment, and architectural and functional design of a new institution-wide Electronic Health Records (EHR). Simultaneously, he was a project leader at the Lausanne Cancer Center where he designed a specialized EHR and research data warehouse to foster translational cancer research. At Geneva Hospital, he was a research scientist (co-principal investigator with Antoine Geissbühler, MD) focusing on chemotherapy protocols integration with a workflow engine to ease management and improve treatment administration security.

Dr. Meystre is a member of the American Medical Informatics Association (AMIA) Publications Committee (2008-2012), chair of the AMIA Natural Language Processing Working Group (2013-), and a member-at-large of the AMIA Clinical Research Informatics Working Group (2009-2013). He is chair of the International Medical Informatics Association HIS workgroup (2013-). He is also member of the Methods of Information in Medicine journal editorial board, a Scientific Program Committee member for the AMIA TBI Summit 2012, the AMIA CRI Summit 2014, and the AAAI 2012 Fall Symposium on Information Retrieval and Knowledge Discovery in Biomedical Text.

“During my residencies in Surgery, Pediatrics, and Pediatric Surgery, I realized how critical it was to have fast, accurate, and ubiquitous access to clinical data and how Electronic Health Records could enhance patient care as well as the work experience of health care practitioners. I also understood how structured data coded with standard terminologies was required for decision support and research, but also how difficult it was for healthcare practitioners to enter data in this format instead of the more natural narrative text format. To alleviate this issue, Natural Language Processing could be used to automatically extract structured and coded data from narrative text—this area of research excited me the most and still does.”

New Lab website: http://meystrelab.org

ResearchGate profile: https://www.researchgate.net/profile/Stephane_Meystre

Google Scholar: http://scholar.google.com/citations?user=AtFItVQAAAAJ&hl=en&oi=sra&language=en

Education History

Type School Degree
Doctoral Training Dept of Medical Informatics, School of Medicine, University of Utah
Medical Informatics
Ph.D.
Graduate Training University of California
Medical Informatics
M.S.
Residency Hopital de la Providence
Surgery
Resident
Residency University Hospital of Lausanne
Pediatric Surgery
Resident
Professional Medical General Surgery examination; University of Lausanne
Surgery
Residency Hopital de la Providence
Surgery
Resident
Residency Hopital du Samaritain
Pediatrics
Resident
Internship University Hospital of Lausanne
Internal Med., Peds., OB/GYN, Ped.Surgery, and Gen. Surgery
Intern
Professional Medical Medical School, University of Lausanne
Medicine
M.D.

Global Impact

Education History

Type School Degree Country
Residency Hopital de la Providence
Surgery
Resident Switzerland
Residency University Hospital of Lausanne
Pediatric Surgery
Resident Switzerland
Professional Medical General Surgery examination; University of Lausanne
Surgery
Switzerland
Residency Hopital de la Providence
Surgery
Resident Switzerland
Residency Hopital du Samaritain
Pediatrics
Resident Switzerland
Internship University Hospital of Lausanne
Internal Med., Peds., OB/GYN, Ped.Surgery, and Gen. Surgery
Intern Switzerland
Professional Medical Medical School, University of Lausanne
Medicine
M.D. Switzerland

Selected Publications

Journal Article

  1. Meystre SM, Kim Y, Gobbel GT, Matheney ME, Redd A, Bray BE, Garvin JH (2016). Congestive heart failure information extraction framework for automated treatment performance measures assessment. J Am Med Inform Assoc.
  2. Khalifa A, Meystre SM (2015). Adapting Existing Natural Language Processing Resources for Cardiovascular Risk Factors Identification in Clinical Notes. J Biomed Inform, 58(S), 128-132.
  3. Meystre, S M, Kim, Y, Heavirland, J, Williams, J, Bray, B E, amp Garvin, J H (2015). Heart Failure Medications Detection and Prescription Status Classification in Clinical Narrative Documents. Stud Health Technol Inform, 216, 609-13.
  4. Kristina Doing-Harris, Yarden Livnat, Stephane Meystre (2015). Automated concept and relationship extraction for the Semi-Automated Ontology Management (SEAM) System. Journal of Biomedical Semantics, 6(15).
  5. Meystre S, Shen S, Hofmann D, Gundlapalli A (2014). Can Physicians Recognize Their Own Patients in De-identified Notes? Stud Health Technol Inform, 205, 778-82.
  6. Ferrandez O, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM (2013). BoB, a best-of-breed automated text de-identification system for VHA clinical documents. J Am Med Inform Assoc, 20(1), 77-83.
  7. Meystre SM, Lee S, Jung CY, Chevrier RD (2012). Common data model for natural language processing based on two existing standard information models: CDA+GrAF. J Biomed Inform, 45(4), 703-10.
  8. Ferrandez O, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM (2012). Evaluating current automatic de-identification methods with Veteran's health administration clinical documents. BMC Med Res Methodol, 12(1), 109.
  9. Kim Y, Hurdle J, Meystre SM (2011). Using UMLS lexical resources to disambiguate abbreviations in clinical text. AMIA Annu Symp Proc, 2011, 715-22.
  10. Meystre SM, Thibault J, Shen S, Hurdle JF, South BR (Sept 2010). Automatically detecting medications and the reason for their prescription in clinical narrative text documents. Stud Health Technol Inform, 160, 944-948.
  11. Meystre SM, Thibault J, Shen S, Hurdle JF, South BR (Sept-Oct 2010). Textractor: a hybrid system for medications and reason for their prescription extraction from clinical text documents. J Am Med Inform Assoc, 17(5), 559-562.
  12. Meystre SM, Friedlin FJ, South BR, Shen S, Samore MH (Aug 2010). Automatic de-identification of textual documents in the electronic health record: a review of recent research. BMC Med Res Methodol, 10, 70.
  13. Meystre SM (2009). Detecting Intuitive Mentions of Diseases in Narrative Clinical Text. Lect Notes Comput Sc, 5651, 216-24.
  14. Meystre SM, Haug PJ (2008). Randomized controlled trial of an automated problem list with improved sensitivity. Int J Med Inform, 77(9), 602-12.
  15. Meystre SM, Savova GK, Kipper-Schuler KC, Hurdle JF (2008). Extracting information from textual documents in the electronic health record: a review of recent research. Yearb Med Inform, 128-44.
  16. Meystre S (2007). Electronic patient records: some answers to the data representation and reuse challenges. Findings from the section on Patient Records. Yearb Med Inform, 46(Suppl 1), 47-9.
  17. Meystre S, Haug PJ (2006). Natural language processing to extract medical problems from electronic clinical documents: performance evaluation. J Biomed Inform, 39(6), 589-99.
  18. Meystre S, Haug P (2006). Improving the sensitivity of the problem list in an intensive care unit by using natural language processing. AMIA Annu Symp Proc, 554-8.
  19. Meystre S (2005). The current state of telemonitoring: a comment on the literature. Telemed J E Health, 11(1), 63-9.
  20. Meystre SM, Mller H (2005). Open source software in the biomedical domain. Swiss Med Informat, 55.
  21. Meystre SM, Haug PJ (2005). Comparing natural language processing tools to extract medical problems from narrative text. AMIA Annu Symp Proc, 525-9.
  22. Meystre S, Haug PJ (2005). Evaluation of Medical Problem Extraction from Electronic Clinical Documents Using MetaMap Transfer (MMTx). Stud Health Technol Inform, 116, 823-8.
  23. Meystre S, Haug PJ (2005). Automation of a problem list using natural language processing. BMC Med Informat Decis Making, 5, 30.
  24. Meystre S, Haug PJ (2003). Medical problem and document model for natural language understanding. AMIA Annu Symp Proc, 455-9.

Book Chapter

  1. Meystre SM, Narus SP, Mitchell JA (2012). Clinical Research in the Postgenomic Era. In R.L. Richesson, J.E. Andrews (Eds.), Clinical Research Informatics (Health Informatics, pp. 113-134). London: Springer-Verlag.

Conference Proceedings

  1. Peter Szolovits, John Aberdeen, Stephane Meystre, Mehmet Kayaalp (2015). State of the Art of Clinical Narrative Report De-Identification and Its Future. AMIA Annu Symp Proc, San Francisco, CA.
  2. Meystre SM, Young K, Redd A, Garvin J (2014). Congestive Heart Failure Information Extraction Framework (CHIEF) Evaluation. AMIA Annu Symp Proc, Washington, DC.
  3. Meystre SM, Ferrandez O, South BR, Shen S, Samore MH (March 2013). How Much Does Automatic Text De-Identification Impact Clinical Problems, Tests, and Treatments? 2013 AMIA Clinical Research Informatics Summit, San Francisco, CA.
  4. Meystre SM, Gouripeddi R, Shah SS, Mitchell JA (March 2013). Automatic Pediatric Pneumonia Characteristics Extraction from Diagnostic Imaging Reports in a Multi-Institutional Clinical Repository. 2013 AMIA Clinical Research Informatics Summit, San Francisco, CA.
  5. Nokes N, Meystre SM, Scehnet JS, South BR, Shen S, Maw M, Ferrandez O, Friedlin FJ, Samore MH (2012). A Survey of VHA Privacy Officers for the External Use of Automatically De- Identified Clinical Documents. AMIA Annu Symp Proc 2012.
  6. Ferrandez O, South BR, Shen S, Meystre SM (June 2012). A Hybrid Stepwise Approach for De-identifying Person Names in Clinical Documents. Proceedings of the 2012 Workshop on Biomedical Natural Language Processing (BioNLP 2012), Montreal, Quebec, Canada, 65-72.
  7. Meystre SM, Kim Y, Garvin JH (March 2012). Comparing Methods for left Ventricular Ejection Fraction Clinical Information Extraction. AMIA Summits Transl Sci Proc, CRI, San Francisco, 138.
  8. South BR, Shen S, Maw M, Ferrandez O, Friedlin FJ, Meystre SM (March 2012). Prevalence Estimates of Clinical Epoynyms in De-Identified Clinical Documents. AMIA Summits Transl Sci Proc, CRI, San Francisco, CA, 158.
  9. Friedlin FJ, South BR, Shen S, Ferrandez O, Nokes N, Maw M, Samore MH, Meystre SM (March 2012). An Evaluation of the Informativeness of De-identified Documents. AMIA Summits Transl Sci Proc, CRI, San Francisco, CA, 117.
  10. Ferrandez O, South BR, Shen S, Maw M, Nokes N, Friedlin FJ, Meystre SM (March 2012). Striving for Optimal Sensitivity to De-identify Clinical Documents. AMIA Summits Transl Sci Proc, CRI, San Francisco, CA, 115.
  11. Ferrandez O, South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM (2012). Generalizability and comparison of automatic clinical text de-identification methods and resources. AMIA Annu Symp Proc, United States, 2012, 199-208.
  12. Shen S, South BR, Friedlin FJ, Meystre SM (2011). Coverage of Manual De-identification on VA Clinical Documents. AMIA Annu Symp Proc 2011, 1958.
  13. Kim Y, Riloff E, Meystre SM (2011). Improving Classification of Medical Assertions in Clinical Notes. 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 311-316.
  14. Meystre SM, Garvin JH, Chapman WW (2010). A Hybrid Information Model to Represent Clinical and Linguistic Data Extracted from Clinical Narrative Documents. AMIA Annu Symp Proc, 1176.
  15. South BR, Shen S, Friedlin FJ, Samore MH, Meystre SM (2010). Enhancing Annotation of Clinical Text using Pre-Annotation of Common PHI. AMIA Annu Symp Proc, 1267.
  16. Kim Y, Hurdle J, Meystre SM (2010). Acronyms and Abbreviations Ambiguity in Clinical Notes. AMIA Annu Symp Proc, 1127.
  17. Meystre SM, Stroup A, Hartz A (2010). A statewide colorectal cancer database in Utah as clinical research use case for the i2b2 hive. AMIA Summit on CRI, San Francisco, CA.
  18. Rocha RA, Hurdle JF, Matney S, Narus SP, Meystre S, LaSalle B, Deshmukh V, Hunter C, Mineau GP, Facelli JC, Mitchell JA (2008). Utah's statewide informatics platform for translational and clinical science. AMIA Annu Symp Proc, United States, 1114.
  19. Meystre SM, Haug PJ (2003). Problem List Management using Natural Language Understanding. SSMI Annual Symposium.

Patent

  1. Meystre SM, Ferrandez O (2014). SYSTEMS AND METHODS FOR EXTRACTING SPECIFIED DATA FROM NARRATIVE TEXT. U.S. Patent No. United States Patent Application 20140350965. Washington, D.C.:U.S. Patent and Trademark Office.

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