Stéphane M. Meystre

3.9k total citations · 1 hit paper
67 papers, 2.4k citations indexed

About

Stéphane M. Meystre is a scholar working on Artificial Intelligence, Molecular Biology and Health Information Management. According to data from OpenAlex, Stéphane M. Meystre has authored 67 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 40 papers in Molecular Biology and 25 papers in Health Information Management. Recurrent topics in Stéphane M. Meystre's work include Biomedical Text Mining and Ontologies (40 papers), Topic Modeling (33 papers) and Electronic Health Records Systems (20 papers). Stéphane M. Meystre is often cited by papers focused on Biomedical Text Mining and Ontologies (40 papers), Topic Modeling (33 papers) and Electronic Health Records Systems (20 papers). Stéphane M. Meystre collaborates with scholars based in United States, Switzerland and Netherlands. Stéphane M. Meystre's co-authors include Peter J. Haug, John F. Hurdle, Guergana Savova, Brett R. South, Shuying Shen, Matthew H. Samore, Young-Jun Kim, Óscar Ferrández, Christoph U. Lehmann and Thomas Bürkle and has published in prestigious journals such as Journal of Medical Internet Research, Journal of the American Medical Informatics Association and BMC Medical Research Methodology.

In The Last Decade

Stéphane M. Meystre

66 papers receiving 2.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Extracting Information from Textual Documents in the Electronic Health Record: A Review of Recent Research

2008 615 citations John F. Hurdle, Stéphane M. Meystre et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Stéphane M. Meystre United States	24	1.4k	1.1k	624	283	235	67	2.4k
Ronald Cornet Netherlands	24	1.1k 0.8×	1.0k 0.9×	573 0.9×	308 1.1×	193 0.8×	163	3.1k
Steven H. Brown United States	25	750 0.5×	926 0.8×	664 1.1×	259 0.9×	145 0.6×	99	2.2k
Brett R. South United States	21	1.6k 1.2×	1.2k 1.1×	309 0.5×	159 0.6×	155 0.7×	54	2.3k
John F. Hurdle United States	21	941 0.7×	776 0.7×	778 1.2×	540 1.9×	114 0.5×	73	3.1k
Peter L. Elkin United States	26	792 0.6×	1.0k 0.9×	814 1.3×	394 1.4×	100 0.4×	159	3.0k
Shuying Shen United States	19	1.3k 1.0×	1.0k 0.9×	270 0.4×	133 0.5×	153 0.7×	55	2.1k
Luke V. Rasmussen United States	24	685 0.5×	671 0.6×	497 0.8×	376 1.3×	60 0.3×	83	2.1k
Li Zhou United States	34	842 0.6×	541 0.5×	558 0.9×	364 1.3×	72 0.3×	172	3.4k
Stanley M. Huff United States	27	1.0k 0.8×	1.5k 1.3×	1.1k 1.8×	356 1.3×	271 1.2×	95	2.6k
C Friedman United States	26	1.5k 1.1×	1.7k 1.5×	487 0.8×	117 0.4×	90 0.4×	43	2.8k

Countries citing papers authored by Stéphane M. Meystre

Since Specialization

Citations

This map shows the geographic impact of Stéphane M. Meystre's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stéphane M. Meystre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stéphane M. Meystre more than expected).

Fields of papers citing papers by Stéphane M. Meystre

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stéphane M. Meystre. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stéphane M. Meystre. The network helps show where Stéphane M. Meystre may publish in the future.

Co-authorship network of co-authors of Stéphane M. Meystre

This figure shows the co-authorship network connecting the top 25 collaborators of Stéphane M. Meystre. A scholar is included among the top collaborators of Stéphane M. Meystre based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stéphane M. Meystre. Stéphane M. Meystre is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Sahoo, Satya S., Joseph M. Plasek, Hua Xu, et al.. (2024). Large language models for biomedicine: foundations, opportunities, challenges, and best practices. Journal of the American Medical Informatics Association. 31(9). 2114–2124. 20 indexed citations

Meystre, Stéphane M., Ruud van Stiphout, Annelies Goris, & Santiago Gaitan. (2023). AI-Based Gut-Brain Axis Digital Twins. Studies in health technology and informatics. 302. 1007–1008. 4 indexed citations

Ford, Dee W., Jillian Harvey, James McElligott, et al.. (2020). Leveraging health system telehealth and informatics infrastructure to create a continuum of services for COVID-19 screening, testing, and treatment. Journal of the American Medical Informatics Association. 27(12). 1871–1877. 40 indexed citations

Kim, Young-Jun & Stéphane M. Meystre. (2019). A Study of Medical Problem Extraction for Better Disease Management. Studies in health technology and informatics. 264. 193–197. 6 indexed citations

Meystre, Stéphane M., et al.. (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. 1 indexed citations

Obeid, Jihad S., et al.. (2019). Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers. Studies in health technology and informatics. 264. 283–287. 15 indexed citations

Meystre, Stéphane M., et al.. (2019). Automatic trial eligibility surveillance based on unstructured clinical data. International Journal of Medical Informatics. 129. 13–19. 44 indexed citations

Garvin, Jennifer H., Young-Jun Kim, Glenn T. Gobbel, et al.. (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–e5. 28 indexed citations

Garvin, Jennifer H., Young-Jun Kim, Paul A. Heidenreich, et al.. (2017). Health Informatics Improves Heart Failure Data Capture for Quality Measures, Research and Decision Support in VA. Journal of Cardiac Failure. 23(8). S113–S113. 1 indexed citations

10.

Velupillai, Sumithra, et al.. (2016). UtahBMI at SemEval-2016 Task 12: Extracting Temporal Information from Clinical Text. 1256–1262. 21 indexed citations

11.

Meystre, Stéphane M., Young-Jun Kim, Andrew Redd, & Jennifer H. Garvin. (2014). Congestive Heart Failure Information Extraction Framework (CHIEF) Evaluation.. AMIA. 2 indexed citations

12.

South, Brett R., Danielle L. Mowery, Óscar Ferrández, et al.. (2012). On the Road Towards Developing a Publicly Available Corpus of De-identified Clinical Texts.. AMIA. 1 indexed citations

13.

Ferrández, Óscar, Brett R. South, Shuying Shen, & Stéphane M. Meystre. (2012). A Hybrid Stepwise Approach for De-identifying Person Names in Clinical Documents. North American Chapter of the Association for Computational Linguistics. 65–72. 7 indexed citations

14.

Ferrández, Óscar, et al.. (2012). BoB, a best-of-breed automated text de-identification system for VHA clinical documents. Journal of the American Medical Informatics Association. 20(1). 77–83. 57 indexed citations

15.

Kim, Young-Jun, Ellen Riloff, & Stéphane M. Meystre. (2011). Improving Classification of Medical Assertions in Clinical Notes. Meeting of the Association for Computational Linguistics. 311–316. 5 indexed citations

16.

Meystre, Stéphane M., et al.. (2011). Common data model for natural language processing based on two existing standard information models: CDA+GrAF. Journal of Biomedical Informatics. 45(4). 703–710. 4 indexed citations

17.

Meystre, Stéphane M., Julien Thibault, Shuying Shen, John F. Hurdle, & Brett R. South. (2010). Automatically detecting medications and the reason for their prescription in clinical narrative text documents.. PubMed. 160(Pt 2). 944–8. 3 indexed citations

18.

Meystre, Stéphane M. & Peter J. Haug. (2008). Randomized controlled trial of an automated problem list with improved sensitivity. International Journal of Medical Informatics. 77(9). 602–612. 43 indexed citations

19.

Meystre, Stéphane M. & Peter J. Haug. (2005). Evaluation of Medical Problem Extraction from Electronic Clinical Documents Using MetaMap Transfer (MMTx).. PubMed. 116. 823–8. 29 indexed citations

20.

Meystre, Stéphane M. & Peter J. Haug. (2005). Natural language processing to extract medical problems from electronic clinical documents: Performance evaluation. Journal of Biomedical Informatics. 39(6). 589–599. 149 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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