Publications

Meystre, S. M., Heider, P. M., Kim, Y., Aruch, D. B., & Britten, C. D. (2019). Automatic trial eligibility surveillance based on unstructured clinical data. International Journal of Medical Informatics, 129, 13–19.
Heider, P., & Meystre, S. M. (2019). A Corpus Munging Tool for Profiling Approaches to Sentence Boundary Detection. In Medinfo 2019. Lyon, France.
Kim, Y., & Meystre, S. M. (2019). A Study of Medical Problem Extraction for Better Disease Management. Studies in Health Technology and Informatics, 264, 193–197.
Obeid, J. S., Heider, P. M., Weeda, E. R., Matuskowitz, A. J., Carr, C. M., Gagnon, K., … Meystre, S. M. (2019). Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers. Studies in Health Technology and Informatics, 264, 283–287.
Heider, P. M., & Meystre, S. M. (2019). Patient-Pivoted Automated Trial Eligibility Pipeline: The First of Three Phases in a Modular Architecture. Studies in Health Technology and Informatics, 264, 1476–1477.
Heider, P., Accetta, J.-K., & Meystre, S. M. (2019). ETUDE: Demonstrating Multiple Matching Styles and Offset Calculators within a Natural Language Processing Evaluation Tool. In Medinfo 2019. Lyon, France.
Kim, Y., & Meystre, S. M. (2019). Ensemble method-based extraction of medication and related information from clinical texts. Journal of the American Medical Informatics Association.
Meystre, S. M., Heider, P., Kim, Y., Aruch, D., & Britten, C. (2019). Automatic Trial Eligibility Surveillance: Pilot Study Focused on Breast Cancer. In AMIA Joint Summits on Translational Science proceedings (pp. 946–947).
Kim, Y., & Meystre, S. M. (2019). Voting Ensemble Pruning for De-identification of Electronic Health Records. In AMIA Joint Summits on Translational Science proceedings (p. 1083).
Meystre, S. M., & Gouripeddi, R. (2019). Clinical Research in the Postgenomic Era. In R. L. Richesson & J. E. Andrews (Eds.), Clinical Research Informatics (pp. 147–168). Cham: Springer.
Heider, P., Accetta, J.-K., & Meystre, S. M. (2018). ETUDE for Easy and Efficient NLP Application Evaluation. In AMIA NLP-WG Pre-Symposium. San Francisco, CA.
Meystre, S., Carrell, D., Hirschman, L., Aberdeen, J., Fearn, P., Petkov, V., & Silverstein, J. C. (2018). Automatic Text De-Identification: How and When is it Acceptable? In AMIA Annu Symp Proc (pp. 124–126). San Francisco, CA. Retrieved from blob:https://knowledge.amia.org/b87966c4-de92-4c73-9568-36fea7e4b65c
Kim, Y., Heider, P., & Meystre, S. M. (2018). Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives. In AMIA Annu Symp Proc (pp. 663–672). San Francisco, CA. Retrieved from blob:https://knowledge.amia.org/c5f7977d-d316-4d6c-8c5a-f1d96b888daf
Kim, Y., Kim, Y., & Meystre, S. M. (2018). Ensemble Method-based Extraction of Medication and Related Information from Clinical Texts. In n2c2 Shared Task and Workshop.
Heider, P., Kim, Y., AAlAbdulsalam, A. K., Kim, C., & Meystre, S. M. (2018). Hybrid Approaches for Automated Clinical Trial Cohort Selection. In n2c2 Shared Task and Workshop (pp. 1–2). San Francisco, CA.
Meystre, S., Heider, P., Heider, Kim, Y., Trice, A., & Underwood, G. (2018). Clinical Text Automatic De-Identification to Support Large Scale Data Reuse and Sharing: Pilot Results. In AMIA Annu Symp Proc (p. 2069). San Francisco, CA. Retrieved from blob:https://knowledge.amia.org/266243dd-77fe-4c70-95d3-c5da534cc0af
Meystre, S. M., Lovis, C., Parra Calderon, C. L., E, W., J, M. A., & Obeid, J. S. (2018). Artificial Intelligence Applications Enabling Clinical Decision Support. In EFMI STC (pp. 1–3). Zagreb, Croatia.
Carter, M., AAlAbdulsalam, A. K., Herget, K., McFadden, S., Garvin, J. H., Redd, A., … Meystre, S. M. (2018). Automated extraction and assignment of TNM stage to support cancer case consolidation. In NAACCR annual conference. Pittsburgh, PA.
AAlAbdulsalam, A. K., Garvin, J. H., Redd, A., Carter, M., Sweeney, C., & Meystre, S. M. (2018). Automated Extraction and Classification of AJCC TNM Stage Mentions from Unstructured Text Fields in a Central Cancer Registry. AMIA Joint Summits on Translational Science Proceedings, 16–25.
Garvin, J. H., Kim, Y., Gobbel, G. T., Matheny, M. E., Redd, A., Bray, B. E., … Meystre, S. M. (2018). Automating Quality Measures for Heart Failure Using Natural Language Processing: A Descriptive Study in the Department of Veterans Affairs. JMIR Medical Informatics, 6(1), e5. https://doi.org/10.2196/medinform.9150
Zhu, V., Walker, T. D., Warren, R. W., Jenny, P. B., Meystre, S. M., & Lenert, L. A. (2017). Identifying Falls Risk Screenings Not Documented with Administrative Codes Using Natural Language Processing. In AMIA Annu Symp Proc (pp. 1906–1913).
Kim, Y., Riloff, E., & Meystre, S. M. (2017). Exploiting Unlabeled Texts with Clustering-based Instance Selection for Medical Relation Classification. In AMIA Annu Symp Proc (pp. 1060–1069). Washington, DC.
Garvin, J. H., Kim, Y., Heidenreich, P., Nativi-Nicolau, J., Inampudi, C., Zeng-Treitler, Q., … Meystre, S. M. (2017). Health Informatics Improves Heart Failure Data Capture for Quality Measures, Research and Decision Support in VA. Journal of Cardiac Failure, 23(8), S113.
Meystre, S. M., & Doing-Harris, K. (2017). Semi-automated Ontology Development and Management System Applied to Medically Unexplained Syndromes in the U.S. Veterans Population. In Artificial Intelligence in Medicine (pp. 345–350). Cham: Springer, Cham. https://doi.org/10.1007/978-3-319-59758-4_41
Meystre, S., Gouripeddi, R., Tieder, J., Simmons, J., Srivastava, R., & Shah, S. (2017). Enhancing Comparative Effectiveness Research With Automated Pediatric Pneumonia Detection in a Multi-Institutional Clinical Repository: A PHIS+ Pilot Study. Journal of Medical Internet Research, 19(5), e162. https://doi.org/10.2196/jmir.6887
Meystre, S. M., Lovis, C., Bürkle, T., Tognola, G., Budrionis, A., & Lehmann, C. U. (2017). Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress. Yearbook of Medical Informatics, 26(1). https://doi.org/10.15265/IY-2017-007
AAlAbdulsalam, A. K., & Meystre, S. M. (2017). Learning to De-Identify Clinical Text with Existing Hybrid Tools. AMIA Summits Transl Sci Proc, 150–151.
Meystre, S., Kim, Y., Gobbel, G., Matheney, M., Redd, A., Bray, B. E., & Garvin, J. H. (2017). Heart Failure Data for Patient Treatment Goals at the Point of Care: Automated Data Extraction and Consistent Reference Standard Importance. AMIA Summits Transl Sci Proc, 370–371.
Kim, Y., Garvin, J. H., Goldstein, M. K., Hwang, T. S., Redd, A., Bolton, D., … Meystre, S. M. (2017). Extraction of Left Ventricular Ejection Fraction Information from Various Types of Clinical Reports. Journal of Biomedical Informatics.
Meystre, S. M., Shao, J., & Jones, G. (2016). Automated Dynamic Problem and Allergy Lists for Efficient Electronic Health Record Management. In AMIA Annu Symp Proc (p. 1512). Chicago, IL.
Khalifa, A., & Meystre, S. M. (2016). Temporally Classifying Clinical Events Relative to Document Creation Time. AMIA Annu Symp Proc, 1–2.
Meystre, S. M., Kim, Y., Gobbel, G. T., Matheny, M. E., Redd, A., Bray, B. E., & Garvin, J. H. (2016). Congestive heart failure information extraction framework for automated treatment performance measures assessment. Journal of the American Medical Informatics Association, ocw097. https://doi.org/10.1093/jamia/ocw097
Khalifa, A., Velupillai, S., & Meystre, S. M. (2016). UtahBMI at SemEval-2016 Task 12: Extracting Temporal Information from Clinical Text. In Proceedings of SemEval- (pp. 1–7). San Diego, CA.
Garvin, J. H., Kim, Y., Gobbel, G. T., Matheny, M. E., Redd, A., Bray, B. E., … Meystre, S. M. (2016). Automated Heart Failure Quality Measurement with Natural Language Processing. Journal of Cardiac \ldots, 22(8S).
Khalifa, A., & Meystre, S. (2015). Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes. Journal of Biomedical Informatics, 1–5. Retrieved from http://dx.doi.org/10.1016/j.jbi.2015.08.002
Kim, Y., Garvin, J., Heavirland, J., & Meystre, S. M. (2015). Improving Detection of Reasons Not to Take a Medication by Leveraging Medication Prescription Status. In AMIA Annu Symp Proc (p. 1528).
Kim, Y., Garvin, J., Goldstein, M. K., & Meystre, S. M. (2015). Classification of Contextual Use of Left Ventricular Ejection Fraction Assessments. Stud Health Technol Inform, 216, 599–603. Retrieved from http://ebooks.iospress.nl/volumearticle/40279
Meystre, S. M., Kim, Y., Heavirland, J., Williams, J., Bray, B. E., & Garvin, J. H. (2015). Heart Failure Medications Detection and Prescription Status Classification in Clinical Narrative Documents. Stud Health Technol Inform, 216, 609–613. Retrieved from http://ebooks.iospress.nl/volumearticle/40281
Meystre, S. M., Lovis, C., Prokosch, H. U., Mykkänen, J., Hripcsak, G., Bürkle, T., & Lehmann, C. U. (2015). eHealth-Enabled Clinical Data Reuse Workshop. In Medinfo 2015. Retrieved from http://www.researchgate.net/profile/Stephane_Meystre/publication/281067421_eHealth-Enabled_Clinical_Data_Reuse/links/561c47d508ae78721fa11335.pdf
Doing-Harris, K., Livnat, Y., & Meystre, S. M. (2015). Automated concept and relationship extraction for the semi-automated ontology management (SEAM) system. Journal of Biomedical Semantics, 6(1), 1–15. Retrieved from http://www.jbiomedsem.com/content/6/1/15
Meystre, S. M., Khalifa, A., Gouripeddi, R., & Rangel, S. D. (2015). Automatic Extraction of Pediatric Acute Appendicitis Treatment Devices from Diagnostic Imaging Reports in a Multi-Institutional Clinical Repository. In AMIA Summits Transl Sci Proc, CRI.
Redd, A., Pickard, S., Meystre, S. M., Scehnet, J. S., ScehnetB, Bolton, D., … Garvin, J. H. (2015). Evaluation of PHI Hunter in Natural Language Processing Research. Perspect Health Inf Manag, Winter 2015. Retrieved from http://perspectives.ahima.org/evaluation-of-phi-hunter-in-natural-language-processing-research/#.VQ7xxVzhbYI
Meystre, S. M. (2015). De-identification of Unstructured Clinical Data for Patient Privacy Protection. In Medical Data Privacy Handbook (pp. 697–716). Cham: Springer International Publishing. Retrieved from http://link.springer.com/chapter/10.1007/978-3-319-23633-9_26/fulltext.html
Meystre, S. M., & Haug, P. J. (2014). Randomized Controlled Trial of an Automated Problem List With Improved Sensitivity. In A. Wright (Ed.), Clinical Problem Lists in the Electronic Health Record (p. 348). CRC Press. Retrieved from http://books.google.ch/books?id=Ao-ZBQAAQBAJ&pg=PA245&dq=Randomized+Controlled+Trial+of+an+Automated+Problem+List+With+Improved+Sensitivity&hl=&cd=1&source=gbs_api
Meystre, S., Kim, Y., Redd, A., & Garvin, J. H. (2014). Congestive Heart Failure Information Extraction Framework (CHIEF) Evaluation. In AMIA Annu Symp Proc (p. 86).
Redd, A., Kim, Y., Meystre, S. M., Heavirland, J., Weaver, A., Wiliams, J., & Garvin, J. H. (2014). Effect of Pre-Annotation on Annotation Time. In AMIA Annu Symp Proc.
South, B. R., Mowery, D. L., Leng, J., Meystre, S. M., & Chapman, W. W. (2014). A System Usability Study Assessing a Machine-Assisted Interactive Interface to Support Annotation of Protected Health Information in Clinical Texts. In AMIA Annu Symp Proc.
South, B. R., Mowery, D., Suo, Y., Leng, J., Ferrandez, O., Meystre, S. M., & Chapman, W. W. (2014). Evaluating the effects of machine pre-annotation and an interactive annotation interface on manual de-identification of clinical text. Journal of Biomedical Informatics, 50, 162–172. Retrieved from http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=24859155&retmode=ref&cmd=prlinks
Meystre, S. M., Ferrandez, O., Friedlin, F. J., South, B. R., Shen, S., & Samore, M. H. (2014). Text de-identification for privacy protection: a study of its impact on clinical text information content. Journal of Biomedical Informatics, 50, 142–150. Retrieved from http://linkinghub.elsevier.com/retrieve/pii/S1532046414000136
Meystre, S. M., Boonsirisumpun, N., Elhadad, N., Savova, G. K., & Chapman, W. W. (2014). Standards-Based Data Model for Clinical Documents and Information in the Shared Annotated Resources (ShARe) Project. In AMIA Summits Transl Sci Proc, CRI (pp. 1–1).

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