World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
80
Citations
43204
World Ranking
1051
National Ranking
562

Zhiyong Lu 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 Zhiyong Lu 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: 276 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Zhiyong Lu 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 Zhiyong Lu 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: 80 D-Index — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Overview

Zhiyong Lu is affiliated with the National Institutes of Health in the United States. Their research intersects multiple scientific fields including computer science, medicine, and biochemistry, genetics, and molecular biology. The main focus of their work revolves around several core topics and methodologies.

The principal research topics covered by Zhiyong Lu include:

  • Biomedical Text Mining and Ontologies
  • Topic Modeling
  • Machine Learning in Healthcare
  • Natural Language Processing Techniques
  • Artificial Intelligence in Healthcare and Education
  • Retinal Imaging and Analysis
  • COVID-19 diagnosis using AI

Within their broad domain, the subfields they contribute to are:

  • Artificial Intelligence
  • Molecular Biology
  • Radiology, Nuclear Medicine and Imaging
  • Ophthalmology
  • Health Informatics

Zhiyong Lu's publication record includes a variety of research venues, with frequent contributions noted in:

  • arXiv (Cornell University)
  • Bioinformatics
  • Nucleic Acids Research
  • Journal of Biomedical Informatics
  • PubMed

Coauthorship collaborations have been significant in their work, partnering frequently with:

  • Qingyu Chen
  • Yifan Peng
  • Qiao Jin
  • Chih-Hsuan Wei
  • Emily Y. Chew

Recent publications by Zhiyong Lu include:

  • Database resources of the national center for biotechnology information, 2021, Nucleic Acids Research
  • Database resources of the National Center for Biotechnology Information, 2020, Nucleic Acids Research
  • Database resources of the National Center for Biotechnology Information in 2023, 2022, Nucleic Acids Research
  • Keep up with the latest coronavirus research, 2020, Nature
  • Opportunities and challenges for ChatGPT and large language models in biomedicine and health, 2023, Briefings in Bioinformatics

Best Publications

  • ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

    Xiaosong Wang;Yifan Peng;Le Lu;Zhiyong Lu

  • Opportunities and obstacles for deep learning in biology and medicine.

    Travers Ching;Daniel S. Himmelstein;Brett K. Beaulieu-Jones;Alexandr A. Kalinin

  • Special Report: NCBI disease corpus: A resource for disease name recognition and concept normalization

    Rezarta Islamaj Doğan;Robert Leaman;Zhiyong Lu

  • Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets.

    Yifan Peng;Shankai Yan;Zhiyong Lu

  • BioCreative V CDR task corpus: a resource for chemical disease relation extraction

    Jiao Li;Yueping Sun;Robin J. Johnson;Daniela Sciaky

  • Database resources of the National Center for Biotechnology Information

    Unknown

  • PubMed and beyond: a survey of web tools for searching biomedical literature.

    Zhiyong Lu

  • PubTator: a web-based text mining tool for assisting biocuration

    Chih Hsuan Wei;Hung Yu Kao;Zhiyong Lu

  • A survey of current trends in computational drug repositioning

    Jiao Li;Si Zheng;Bin Chen;Atul J. Butte

  • TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-Rays

    Xiaosong Wang;Yifan Peng;Le Lu;Zhiyong Lu

  • DNorm: disease name normalization with pairwise learning to rank.

    Robert Leaman;Rezarta Islamaj Doğan;Zhiyong Lu

  • Predicting subcellular localization of proteins using machine-learned classifiers

    Z. Lu;D. Szafron;R. Greiner;P. Lu

  • BioWordVec, improving biomedical word embeddings with subword information and MeSH.

    Yijia Zhang;Yijia Zhang;Qingyu Chen;Zhihao Yang;Hongfei Lin

  • PubTator central: automated concept annotation for biomedical full text articles

    Chih-Hsuan Wei;Alexis Allot;Robert Leaman;Zhiyong Lu

  • Overview of BioCreative II gene normalization.

    Alexander A. Morgan;Zhiyong Lu;Xinglong Wang;Aaron M. Cohen

  • The CHEMDNER corpus of chemicals and drugs and its annotation principles.

    Martin Krallinger;Obdulia Rabal;Florian Leitner;Miguel Vazquez

  • Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task

    Chih-Hsuan Wei;Yifan Peng;Robert Leaman;Allan Peter Davis

  • TaggerOne: joint named entity recognition and normalization with semi-Markov Models

    Robert Leaman;Zhiyong Lu

  • Understanding PubMed® user search behavior through log analysis

    Rezarta Islamaj Dogan;G. Craig Murray;Aurélie Névéol;Zhiyong Lu

  • Keep up with the latest coronavirus research.

    Qingyu Chen;Alexis Allot;Zhiyong Lu

  • ChestX-ray: Hospital-Scale Chest X-ray Database and Benchmarks on Weakly Supervised Classification and Localization of Common Thorax Diseases.

    Xiaosong Wang;Yifan Peng;Le Lu;Zhiyong Lu

  • Database resources of the National Center for Biotechnology Information

    Unknown

Frequent Co-Authors

Chih-Hsuan Wei
Chih-Hsuan Wei National Institutes of Health
W. John Wilbur
W. John Wilbur National Institutes of Health
Ronald M. Summers
Ronald M. Summers National Institutes of Health
Emily Y. Chew
Emily Y. Chew National Institutes of Health
Cecilia N. Arighi
Cecilia N. Arighi University of Delaware
Le Lu
Le Lu Alibaba Group (China)
Cathy H. Wu
Cathy H. Wu University of Delaware
Hong-Jie Dai
Hong-Jie Dai Southwest University
Martin Krallinger
Martin Krallinger Barcelona Supercomputing Center
K. Bretonnel Cohen
K. Bretonnel Cohen University of Colorado Denver

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