World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
6481
World Ranking
6254
National Ranking
1728

Peter J. Haug publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Peter J. Haug sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 195 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Peter J. Haug D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Peter J. Haug sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Peter J. Haug is affiliated with the University of Utah in the United States. Their research spans several fields of study including Medicine, Health Professions, and Biochemistry, Genetics and Molecular Biology. Within these areas, subfields of particular focus are Health Information Management, Molecular Biology, Artificial Intelligence, Epidemiology, and Information Systems and Management.

The main topics covered by their work include Electronic Health Records Systems, Biomedical Text Mining and Ontologies, Machine Learning in Healthcare, Scientific Computing and Data Management, Semantic Web and Ontologies, Health Systems, Economic Evaluations, Quality of Life, and Research Data Management Practices.

Recent published papers by Peter J. Haug include the following:

  • "Contemporary clinical decision support standards using Health Level Seven International Fast Healthcare Interoperability Resources," 2021, Journal of the American Medical Informatics Association
  • "Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions," 2020, Journal of the American Medical Informatics Association
  • "Categorizing metadata to help mobilize computable biomedical knowledge," 2021, Learning Health Systems
  • "Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial," 2021, Trials
  • "Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy," 2022, Journal of the American Medical Informatics Association

Frequent publication venues for Peter J. Haug include:

  • Journal of the American Medical Informatics Association
  • Learning Health Systems
  • Trials
  • Journal of Thoracic Imaging
  • Journal of the American College of Emergency Physicians Open

Collaborative work is evident with frequent co-authors such as Robert A. Jenders, Stanley M. Huff, Bryn Rhodes, Guilherme Del Fiol, and Kensaku Kawamoto.

Best Publications

  • Forecasting daily patient volumes in the emergency department.

    Spencer S. Jones;Alun Thomas;R. Scott Evans;R. Scott Evans;Shari J. Welch

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

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

  • Natural language processing to extract medical problems from electronic clinical documents: Performance evaluation

    Stéphane Meystre;Peter J. Haug

  • Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data

    Susan Rea;Jyotishman Pathak;Guergana Savova;Thomas A. Oniki

  • The Arden Syntax for Medical Logic Modules.

    Hripcsak G;Clayton Pd;Pryor Ta;Haug P

  • 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

  • A multivariate time series approach to modeling and forecasting demand in the emergency department

    Spencer S. Jones;R. Scott Evans;Todd L. Allen;Alun Thomas

  • An Event Model of Medical Information Representation

    Stanley M. Huff;Roberto A. Rocha;Bruce E. Bray;Homer R. Warner

  • Exploiting missing clinical data in Bayesian network modeling for predicting medical problems

    Jau-Huei Lin;Peter J. Haug

  • Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium

    Jyotishman D Pathak;Kent R Bailey;Calvin E. Beebe;Steven Bethard

  • Computerized extraction of coded findings from free-text radiologic reports. Work in progress.

    P J Haug;D L Ranum;P R Frederick

  • Building a comprehensive clinical information system from components. The approach at Intermountain Health Care.

    Paul D. Clayton;S. P. Narus;S. M. Huff;T. A. Pryor

  • Decision support in medicine: examples from the HELP system

    Peter J. Haug;Reed M. Gardner;Karen E. Tate;R. Scott Evans

  • MPLUS: a probabilistic medical language understanding system

    Lee Christensen;Peter Haug;Marcelo Fiszman

  • ILIAD as an Expert Consultant to Teach Differential Diagnosis

    Homer R. Warner;Peter Haug;Omar Bouhaddou;Michael Lincoln

  • A Comparison of Classification Algorithms to Automatically Identify Chest X-Ray Reports That Support Pneumonia

    Wendy Webber Chapman;Marcelo Fizman;Brian E Chapman;Peter J Haug

  • Automation of a problem list using natural language processing.

    Stéphane M. Meystre;Peter J. Haug

  • Experience with a mixed semantic/syntactic parser.

    P. J. Haug;S. Koehler;L. M. Lau;P. Wang

  • Assessing the quality of clinical data in a computer-based record for calculating the pneumonia severity index.

    Dominik Aronsky;Peter J. Haug

  • Effectiveness of topic-specific infobuttons: a randomized controlled trial

    Guilherme Del Fiol;Guilherme Del Fiol;Peter J. Haug;Peter J. Haug;James J. Cimino;Scott P. Narus

Frequent Co-Authors

Stanley M. Huff
Stanley M. Huff University of Utah
Wendy W. Chapman
Wendy W. Chapman University of Melbourne
Michael Wagner
Michael Wagner TU Dresden
Robert A. Greenes
Robert A. Greenes Arizona State University
Gregory F. Cooper
Gregory F. Cooper University of Pittsburgh
Randall W. Burt
Randall W. Burt University of Utah
Lisa A. Cannon-Albright
Lisa A. Cannon-Albright University of Utah
Christopher G. Chute
Christopher G. Chute Johns Hopkins University
Jyotishman Pathak
Jyotishman Pathak Cornell University
Hongfang Liu
Hongfang Liu The University of Texas Health Science Center at Houston

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