World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
12662
World Ranking
4296
National Ranking
128

Wendy W. Chapman publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Wendy W. Chapman sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 192 publications — 43rd percentile

43% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Wendy W. Chapman D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Wendy W. Chapman sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Wendy W. Chapman is affiliated with the University of Melbourne in Australia. Their research primarily focuses on medicine and health professions, with substantial contributions to the fields of general health professions and public health, environmental and occupational health.

Their scholarly output includes a substantial number of publications related to telemedicine and telehealth implementation, mobile health and mHealth applications, as well as digital mental health interventions. Additional areas of interest cover heart failure treatment and management, healthcare systems and technology, health systems economic evaluations, and health disparities and outcomes.

Frequent venues for their publications include Studies in Health Technology and Informatics, where they have contributed six papers, followed by BMC Health Services Research with three publications. Other regular venues are the Journal of Biomedical Informatics, JAMIA Open, and JAMA Network Open, each hosting multiple papers.

Wendy W. Chapman has collaborated extensively with several researchers. Frequent co-authors include Daniel Capurro with ten joint works, Kara Burns with seven, Kayley Lyons with seven, Mahima Kalla with seven, and Kit Huckvale with six publications.

The scientist's recent notable papers are as follows:

  • Implementability of healthcare interventions: an overview of reviews and development of a conceptual framework, 2022, Implementation Science
  • A Proposed Framework on Integrating Health Equity and Racial Justice into the Artificial Intelligence Development Lifecycle, 2021, Journal of Health Care for the Poor and Underserved
  • Comparative Effectiveness of Carotid Endarterectomy vs Initial Medical Therapy in Patients With Asymptomatic Carotid Stenosis, 2020, JAMA Neurology
  • Artificial Intelligence and Deep Learning for Rheumatologists, 2022, Arthritis & Rheumatology
  • Establishing a multidisciplinary initiative for interoperable electronic health record innovations at an academic medical center, 2021, JAMIA Open

Best Publications

  • Natural language processing: an introduction.

    Prakash M. Nadkarni;Lucila Ohno-Machado;Wendy Webber Chapman

  • A simple algorithm for identifying negated findings and diseases in discharge summaries

    Wendy Webber Chapman;Will Bridewell;Paul Hanbury;Gregory F. Cooper

  • Methodological Review: What can natural language processing do for clinical decision support?

    Dina Demner-Fushman;Wendy W. Chapman;Clement J. McDonald

  • ConText: An algorithm for determining negation, experiencer, and temporal status from clinical reports

    Henk Harkema;John N. Dowling;Tyler Thornblade;Wendy W. Chapman

  • Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products

    Mark Myslín;Shu Hong Zhu;Wendy Chapman;Mike Conway

  • Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions

    Wendy Webber Chapman;Prakash M. Nadkarni;Lynette Hirschman;Leonard W. D'Avolio;Leonard W. D'Avolio

  • Automatic Detection of Acute Bacterial Pneumonia from Chest X-ray Reports

    M Fiszman;W W Chapman;D Aronsky;R S Evans

  • Overview of the ShARe/CLEF eHealth Evaluation Lab 2013

    Hanna Suominen;Sanna Salanterä;Sumithra Velupillai;Wendy W. Chapman

  • Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances

    Sumithra Velupillai;Sumithra Velupillai;Hanna Suominen;Hanna Suominen;Maria Liakata;Angus Roberts

  • Evaluation of negation phrases in narrative clinical reports.

    Wendy W. Chapman;Will Bridewell;Paul Hanbury;Gregory F. Cooper

  • Classifying free-text triage chief complaints into syndromic categories with natural languages processing

    Wendy W. Chapman;Lee M. Christensen;Michael M. Wagner;Peter J. Haug

  • SemEval-2015 Task 14: Analysis of Clinical Text

    Noémie Elhadad;Sameer Pradhan;Sharon Gorman;Suresh Manandhar

  • Using Natural Language Processing to Improve Efficiency of Manual Chart Abstraction in Research: The Case of Breast Cancer Recurrence

    David S. Carrell;Scott Halgrim;Diem Thy Tran;Diana S M Buist

  • ConText: An Algorithm for Identifying Contextual Features from Clinical Text

    Wendy Chapman;John Dowling;David Chu

  • Public sharing of research datasets: a pilot study of associations

    Heather A. Piwowar;Wendy Webber Chapman

  • Automated syndromic surveillance for the 2002 Winter Olympics.

    Per H. Gesteland;Reed M. Gardner;Fu-Chiang Tsui;Jeremy U. Espino

  • Evaluating the state of the art in disorder recognition and normalization of the clinical narrative.

    Sameer Pradhan;Noémie Elhadad;Brett R. South;David Martínez

  • Overview of the ShARe/CLEF eHealth evaluation lab 2014

    Liadh Kelly;Lorraine Goeuriot;Hanna Suominen;Tobias Schreck

  • Analysis of Web access logs for surveillance of influenza.

    Heather A. Johnson;Michael M. Wagner;William R. Hogan;Wendy W. Chapman

  • Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm

    Brian E. Chapman;Sean Lee;Hyunseok Peter Kang;Wendy W. Chapman

  • iDASH: integrating data for analysis, anonymization, and sharing

    Lucila Ohno-Machado;Vineet Bafna;Aziz A Boxwala;Brian E Chapman

  • A common type system for clinical natural language processing

    Stephen T Wu;Vinod C Kaggal;Dmitriy Dligach;James J Masanz

Frequent Co-Authors

Guergana Savova
Guergana Savova Harvard University
Peter J. Haug
Peter J. Haug University of Utah
Michael Wagner
Michael Wagner TU Dresden
Sameer Pradhan
Sameer Pradhan Vassar College
Noémie Elhadad
Noémie Elhadad Columbia University
Gregory F. Cooper
Gregory F. Cooper University of Pittsburgh
Janyce Wiebe
Janyce Wiebe University of Pittsburgh
Matthew H. Samore
Matthew H. Samore University of Utah
Bruce G. Buchanan
Bruce G. Buchanan University of Pittsburgh
Guido Zuccon
Guido Zuccon University of Queensland

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