World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
13507
World Ranking
3631
National Ranking
1741

Samson W. Tu 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 Samson W. Tu 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: 197 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Samson W. Tu 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 Samson W. Tu 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

Samson W. Tu is affiliated with Stanford University in the United States, working primarily in the field of Medicine. Their research spans several subfields, including Epidemiology, Health Information Management, Economics and Econometrics, Molecular Biology, and Genetics.

Their research topics concentrate on Chronic Disease Management Strategies, Medical Coding and Health Information, Biomedical Text Mining and Ontologies, Health Systems, Economic Evaluations, Quality of Life, Genomics and Rare Diseases, Clinical Practice Guidelines Implementation, and Pharmaceutical Practices and Patient Outcomes.

The scientist has contributed to a range of papers including the following:

  • Towards a goal-oriented methodology for clinical-guideline-based management recommendations for patients with multimorbidity: GoCom and its preliminary evaluation, 2020, Journal of Biomedical Informatics
  • A community-of-practice-based evaluation methodology for knowledge intensive computational methods and its application to multimorbidity decision support, 2023, Journal of Biomedical Informatics
  • Toward a Harmonized WHO Family of International Classifications Content Model, 2020, Studies in health technology and informatics
  • Harmonization of ICF Body Structures and ICD-11 Anatomic Detail: One foundation for multiple classifications, 2023, PLoS ONE
  • Towards a framework for comparing functionalities of multimorbidity clinical decision support: A literature-based feature set and benchmark cases., 2022, PubMed

Frequent coauthors working with Samson W. Tu include:

  • Mor Peleg
  • Alexandra Kogan
  • Irit Hochberg
  • William Van Woensel
  • Wojtek Michalowski

Samson W. Tu's publications often appear in the following venues:

  • Journal of Biomedical Informatics
  • Studies in health technology and informatics
  • Zenodo (CERN European Organization for Nuclear Research)
  • PLoS ONE
  • Pain

Best Publications

  • The evolution of Protégé: an environment for knowledge-based systems development

    John H. Gennari;Mark A. Musen;Ray W. Fergerson;William E. Grosso

  • Comparing computer-interpretable guideline models: a case-study approach.

    Mor Peleg;Samson W. Tu;Jonathan Bury;Paolo Ciccarese

  • The guideline interchange format: a model for representing guidelines.

    Lucila Ohno-Machado;John H. Gennari;Shawn N. Murphy;Nilesh L. Jain

  • EON: A Component-Based Approach to Automation of Protocol-Directed Therapy

    Mark A. Musen;Samson W. Tu;Amar K. Das;Yuval Shahar

  • Knowledge modeling at the millennium : The design and evolution of Protégé-2000

    William Grosso;Henrik Eriksson;Ray Fergerson;John Gennari

  • GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines

    Aziz A. Boxwala;Mor Peleg;Samson Tu;Omolola Ogunyemi

  • GLIF3: the evolution of a guideline representation format.

    Mor Peleg;Aziz A. Boxwala;Omolola Ogunyemi;Qing T. Zeng

  • Supporting rule system interoperability on the semantic web with SWRL

    Martin O'connor;Holger Knublauch;Samson Tu;Benjamin Grosof

  • Protégé-2000: an open-source ontology-development and knowledge-acquisition environment.

    Natalya F Noy;Monica Crubezy;Ray W Fergerson;Holger Knublauch

  • A multiple-method knowledge-acquisition shell for the automatic generation of knowledge-acquisition tools

    Angel R. Puerta;John W. Egar;Samson W. Tu;Mark A. Musen

  • The SAGE Guideline Model: Achievements and Overview

    Samson W. Tu;James R. Campbell;Julie Glasgow;Mark A. Nyman

  • Task modeling with reusable problem-solving methods

    Henrik Eriksson;Yuval Shahar;Samson W. Tu;Angel R. Puerta

  • Supporting Collaborative Ontology Development in Protégé

    Tania Tudorache;Natalya F. Noy;Samson Tu;Mark A. Musen

  • Formal representation of eligibility criteria

    Chunhua Weng;Samson W. Tu;Ida Sim;Rachel Richesson

  • Using scenarios in chronic disease management guidelines for primary care.

    Peter D. Johnson;Samson W. Tu;Nick Booth;Bob Sugden

  • Mapping domains to methods in support of reuse

    John H. Gennari;Samson W. Tu;Thomas E. Rothenfluh;Mark A. Musen

  • Representation primitives, process models and patient data in computer-interpretable clinical practice guidelines: a literature review of guideline representation models.

    Dongwen Wang;Mor Peleg;Samson W Tu;Aziz A Boxwala

  • Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

    Samson W Tu;Henrik Eriksson;John H Gennari;Yuval Shahar

  • A flexible approach to guideline modeling.

    Samson W. Tu;Mark A. Musen

  • Modeling data and knowledge in the EON guideline architecture.

    Samson W. Tu;Mark A. Musen

  • Protégé-2000: An Open-Source Ontology-Development and Knowledge-Acquisition Environment: AMIA 2003 Open Source Expo

    Natalya Fridman Noy;Monica Crubézy;Ray W. Fergerson;Holger Knublauch

  • GLIF3: A Representation Format for Sharable Computer-Interpretable Clinical Practice

    Aziz A. Boxwala;Mor Peleg;Samson W. Tu;Omolola Ijeoma Ogunyemi

Frequent Co-Authors

Mark A. Musen
Mark A. Musen Stanford University
Mor Peleg
Mor Peleg University of Haifa
Edward H. Shortliffe
Edward H. Shortliffe Columbia University
Robert A. Greenes
Robert A. Greenes Arizona State University
Yuval Shahar
Yuval Shahar Ben-Gurion University of the Negev
John H. Gennari
John H. Gennari University of Washington
Vimla L. Patel
Vimla L. Patel Columbia University
Natalya F. Noy
Natalya F. Noy Google (United States)
Elmer V. Bernstam
Elmer V. Bernstam The University of Texas Health Science Center at Houston
Paul A. Heidenreich
Paul A. Heidenreich Stanford University

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