World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
12912
World Ranking
3447
National Ranking
1666

Guergana Savova 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 Guergana Savova 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: 182 publications — 39th percentile

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

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

Guergana Savova 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 Guergana Savova 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: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Overview

Guergana Savova is affiliated with Harvard University in the United States. Their research integrates fields of medicine and computer science, focusing heavily on artificial intelligence applications within healthcare.

The scientist's main fields of study include Medicine and Computer Science. Within these areas, their work extends into several specialized subfields such as Artificial Intelligence, Neurology, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, and Health Informatics.

Savova's research topics cover a diverse range of subjects, including:

  • Topic Modeling
  • Machine Learning in Healthcare
  • Artificial Intelligence in Healthcare and Education
  • Radiomics and Machine Learning in Medical Imaging
  • Biomedical Text Mining and Ontologies
  • Intracranial Aneurysms: Treatment and Complications
  • Cerebrovascular and Carotid Artery Diseases

Notable recent publications include:

  • "Large language models to identify social determinants of health in electronic health records," 2024, npj Digital Medicine
  • "Use of Artificial Intelligence Chatbots for Cancer Treatment Information," 2023, JAMA Oncology
  • "The TRIPOD-LLM reporting guideline for studies using large language models," 2025, Nature Medicine
  • "Evaluating the ChatGPT family of models for biomedical reasoning and classification," 2024, Journal of the American Medical Informatics Association
  • "Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer," 2021, International Journal of Radiation Oncology*Biology*Physics

Savova's frequent coauthors include Danielle S. Bitterman, Sean Finan, Raymond H. Mak, Dmitriy Dligach, and Hugo J.W.L. Aerts.

Key publication venues where Savova has contributed multiple works include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • International Journal of Radiation Oncology*Biology*Physics
  • JCO Clinical Cancer Informatics
  • Scientific Reports

Best Publications

  • Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications

    Guergana K Savova;James J Masanz;Philip V Ogren;Jiaping Zheng

  • Extracting information from textual documents in the electronic health record: a review of recent research.

    S. M. Meystre;G. K. Savova;K. C. Kipper-Schuler;J. F. Hurdle

  • PheKB: A catalog and workflow for creating electronic phenotype algorithms for transportability

    Jacqueline Kirby;Peter Speltz;Luke V. Rasmussen;Melissa A. Basford

  • 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

  • Overview of the ShARe/CLEF eHealth Evaluation Lab 2013

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

  • Clinical Natural Language Processing in languages other than English: opportunities and challenges

    Aurélie Névéol;Hercules Dalianis;Sumithra Velupillai;Sumithra Velupillai;Guergana Savova

  • Development of phenotype algorithms using electronic medical records and incorporating natural language processing

    Katherine P Liao;Katherine P Liao;Tianxi Cai;Guergana K Savova;Shawn N Murphy

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

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

  • SemEval-2016 Task 12: Clinical TempEval

    Steven Bethard;Guergana Savova;Wei-Te Chen;Leon Derczynski

  • Temporal Annotation in the Clinical Domain

    William F. Styler;Steven Bethard;Sean Finan;Martha Palmer

  • The emerging role of electronic medical records in pharmacogenomics

    R. A. Wilke;H. Xu;J. C. Denny;D. M. Roden

  • Automatically extracting cancer disease characteristics from pathology reports into a Disease Knowledge Representation Model

    Anni Coden;Guergana Savova;Igor Sominsky;Michael Tanenblatt

  • 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

  • SemEval-2015 Task 6: Clinical TempEval

    Steven Bethard;Leon Derczynski;Guergana Savova;James Pustejovsky

  • Improving case definition of Crohn's disease and ulcerative colitis in electronic medical records using natural language processing: a novel informatics approach.

    Ashwin N. Ananthakrishnan;Tianxi Cai;Guergana Savova;Su Chun Cheng

  • Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records

    Guergana K Savova;Ioana Danciu;Folami Alamudun;Timothy Miller;Timothy Miller

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

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

  • Towards comprehensive syntactic and semantic annotations of the clinical narrative.

    Daniel Albright;Arrick Lanfranchi;Anwen Fredriksen;William F. Styler

  • Leveraging informatics for genetic studies: use of the electronic medical record to enable a genome-wide association study of peripheral arterial disease

    Iftikhar J Kullo;Jin Fan;Jyotishman Pathak;Guergana K Savova

  • A common type system for clinical natural language processing

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

Frequent Co-Authors

Isaac S. Kohane
Isaac S. Kohane Harvard University
Elizabeth W. Karlson
Elizabeth W. Karlson Brigham and Women's Hospital
Christopher G. Chute
Christopher G. Chute Johns Hopkins University
Wendy W. Chapman
Wendy W. Chapman University of Melbourne
Steven Bethard
Steven Bethard University of Arizona
Robert M. Plenge
Robert M. Plenge Bristol Myers Squibb
Ashwin N. Ananthakrishnan
Ashwin N. Ananthakrishnan Harvard University
Sameer Pradhan
Sameer Pradhan Vassar College
Scott T. Weiss
Scott T. Weiss Harvard University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education can open doors to various Computer Science careers, whether you’re starting out or looking to advance your skills. Many students find easy online associate degrees to be a practical entry point. These programs typically offer flexibility and a fast track to basic IT jobs, making them ideal for those seeking a quicker start.

Affordability is another key factor. The university of north georgia is recognized for its low-cost online programs, offering quality education for budget-conscious learners. Similarly, students should consider online schools that are nationally accredited for broader acceptance of their degree in the job market.

For those interested in gaming and creative technology, pursuing an online school for game design is an excellent way to acquire specialized skills. Ultimately, choosing the right online pathway can provide valuable credentials and open up diverse opportunities in the ever-evolving field of computer science.

Best Scientists Citing Guergana Savova

Trending Scientists

Recently Published Articles