World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
11402
World Ranking
3884
National Ranking
1838

Robert M. Nishikawa 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 Robert M. Nishikawa 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: 297 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Robert M. Nishikawa 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 Robert M. Nishikawa 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2017 - SPIE Fellow

Overview

Robert M. Nishikawa is affiliated with the University of Pittsburgh in the United States. Their research spans multiple disciplines within medicine and computer science, with a strong focus on artificial intelligence applications in medical imaging and oncology.

The scholar's work predominantly addresses topics related to:

  • AI in cancer detection
  • Radiomics and machine learning in medical imaging
  • Global cancer incidence and screening
  • Digital radiography and breast imaging
  • Artificial intelligence in healthcare and education
  • Breast cancer treatment studies
  • Generative adversarial networks and image synthesis

Main fields of study in which they have contributed include:

  • Medicine
  • Computer Science

Subfields of study in their publications feature:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Oncology
  • Pulmonary and Respiratory Medicine
  • Computer Vision and Pattern Recognition

Frequent publication venues where their work appears are:

  • Journal of Medical Imaging
  • Journal of Breast Imaging
  • Radiology
  • Journal of Clinical Oncology
  • Medical Imaging 2022: Computer-Aided Diagnosis

Their research includes studies on breast cancer detection, imaging technologies, and AI applications in clinical settings. Notable papers include:

  • Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis (2023), published in Radiology
  • Cross-Organ, Cross-Modality Transfer Learning: Feasibility Study for Segmentation and Classification (2020), published in IEEE Access
  • Virtual Clinical Trials: Why and What (Special Section Guest Editorial) (2020), published in Journal of Medical Imaging
  • Developing breast lesion detection algorithms for digital breast tomosynthesis: Leveraging false positive findings (2022), published in Medical Physics
  • Use of Artificial Intelligence for Digital Breast Tomosynthesis Screening: A Preliminary Real-world Experience (2023), published in Journal of Breast Imaging

Several frequent co-authors have collaborated with Robert M. Nishikawa, including:

  • Juhun Lee
  • Margarita L. Zuley
  • Andriy I. Bandos
  • Durwin Logue
  • Emily F. Conant

In 2017, Robert M. Nishikawa was recognized as a SPIE Fellow.

Best Publications

  • A support vector machine approach for detection of microcalcifications

    I. El-Naqa;Yongyi Yang;M.N. Wernick;N.P. Galatsanos

  • Improving breast cancer diagnosis with computer-aided diagnosis

    Yulei Jiang;Robert M. Nishikawa;Robert A. Schmidt;Charles E. Metz

  • A study on several Machine-learning methods for classification of Malignant and benign clustered microcalcifications

    Liyang Wei;Yongyi Yang;R.M. Nishikawa;Yulei Jiang

  • A similarity learning approach to content-based image retrieval: application to digital mammography

    I. El-Naqa;Yongyi Yang;N.P. Galatsanos;R.M. Nishikawa

  • A receiver operating characteristic partial area index for highly sensitive diagnostic tests

    Y Jiang;C E Metz;R M Nishikawa

  • Malignant and benign clustered microcalcifications: automated feature analysis and classification.

    Y Jiang;R M Nishikawa;D E Wolverton;C E Metz

  • Computer-aided diagnosis in radiology: potential and pitfalls

    Kunio Doi;Heber MacMahon;Shigehiko Katsuragawa;Robert M Nishikawa

  • Current status and future directions of computer-aided diagnosis in mammography

    Robert M. Nishikawa

  • Task-based assessment of breast tomosynthesis: effect of acquisition parameters and quantum noise.

    I. Reiser;R. M. Nishikawa

  • Methods for improving the accuracy in differential diagnosis on radiologic examinations

    Robert M. Nishikawa;Yulei Jiang;Kazuto Ashizawa;Kunio Doi

  • Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network

    Wei Zhang;Kunio Doi;Maryellen L. Giger;Yuzheng Wu

  • Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms.

    Emil Y. Sidky;Xiaochuan Pan;Ingrid S. Reiser;Robert M. Nishikawa

  • Computerized detection of clustered microcalcifications in digital mammograms: applications of artificial neural networks.

    Yuzheng Wu;Kunio Doi;Maryellen L. Giger;Robert M. Nishikawa

  • Effect of case selection on the performance of computer-aided detection schemes.

    Robert M. Nishikawa;Maryellen L. Giger;Kunio Doi;Charles E. Metz

  • Relevance vector machine for automatic detection of clustered microcalcifications

    Liyang Wei;Yongyi Yang;R.M. Nishikawa;M.N. Wernick

  • Potential of Computer-aided Diagnosis to Reduce Variability in Radiologists’ Interpretations of Mammograms Depicting Microcalcifications

    Yulei Jiang;Robert M. Nishikawa;Robert A. Schmidt;Alicia Y. Toledano

  • Scanned-projection digital mammography.

    Robert M. Nishikawa;Robert M. Nishikawa;Gordon E. Mawdsley;Gordon E. Mawdsley;Aaron Fenster;Aaron Fenster;Martin J. Yaffe;Martin J. Yaffe

  • Computer-aided method for image feature analysis and diagnosis in mammography

    Robert M. Nishikawa;Takehiro Ema;Hiroyuki Yoshida;Kunio Doi

  • Automated segmentation of digitized mammograms

    Ulrich Bick;Maryellen L. Giger;Robert A. Schmidt;Robert M. Nishikawa

  • Toward consensus on quantitative assessment of medical imaging systems.

    Charles E. Metz;Robert F. Wagner;Kunio Doi;David G. Brown

  • MALIGNANT AND BENIGN CLUSTERED MICROCALCIFICATIONS : AUTOMATED FEATURE ANALYSIS AND CLASSIFICATION. AUTHORS' REPLY

    G. A. P. De Kort;D. Beijerinck;J. J. M. Deurenberg;Y. Jiang

Frequent Co-Authors

Maryellen L. Giger
Maryellen L. Giger University of Chicago
Kunio Doi
Kunio Doi University of Chicago
Yongyi Yang
Yongyi Yang Illinois Institute of Technology
Charles E. Metz
Charles E. Metz University of Chicago
Miles N. Wernick
Miles N. Wernick Illinois Institute of Technology
Martin J. Yaffe
Martin J. Yaffe University of Toronto
Daniel B. Kopans
Daniel B. Kopans Harvard University
Emil Y. Sidky
Emil Y. Sidky University of Chicago
Heber MacMahon
Heber MacMahon University of Chicago
Xiaochuan Pan
Xiaochuan Pan University of Chicago

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