World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
68
Citations
23562
World Ranking
2053
National Ranking
1038

Sandy Napel 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 Sandy Napel 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: 213 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Sandy Napel 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 Sandy Napel 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: 68 D-Index — 86th percentile

86% of scientists in this discipline score the same or lower.

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

Overview

Sandy Napel is affiliated with Stanford University in the United States and specializes in Medicine, with a significant focus on Radiology, Nuclear Medicine and Imaging. Their research portfolio spans several subfields including Pulmonary and Respiratory Medicine, Artificial Intelligence, Health Informatics, and Biomedical Engineering.

Their primary topics of work include:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Artificial Intelligence in Healthcare and Education
  • Lung Cancer Diagnosis and Treatment
  • Advanced X-ray and CT Imaging
  • Sarcoma Diagnosis and Treatment
  • COVID-19 diagnosis using AI

Among Sandy Napel's notable recent papers are:

  • "The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping" (2020) published in Radiology
  • "The Medical Segmentation Decathlon" (2022) published in Nature Communications
  • "Artificial intelligence and machine learning in cancer imaging" (2022) published in Communications Medicine
  • "FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare" (2025) published in BMJ
  • "A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets" (2020) published in Nature Machine Intelligence

Frequent co-authors collaborating with Sandy Napel include:

  • Sarah A. Mattonen
  • Olivier Gevaert
  • Spyridon Bakas
  • Keyvan Farahani
  • M. Jorge Cardoso

The scientist's work has appeared frequently in several publication venues such as:

  • Journal of Medical Imaging
  • arXiv (Cornell University)
  • Tomography
  • Journal of Clinical Oncology
  • Radiology

Sandy Napel's research involves interdisciplinary efforts integrating advanced imaging techniques and artificial intelligence to improve diagnostic and prognostic capabilities, particularly in the context of cancer and respiratory diseases. Their work on radiomics and machine learning contributes to the development of standardized quantitative methods for high-throughput image analysis.

Best Publications

  • The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

    Alex Zwanenburg;Alex Zwanenburg;Martin Vallières;Mahmoud A. Abdalah;Hugo J. W. L. Aerts;Hugo J. W. L. Aerts

  • Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

    Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky

  • Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques

    West J;Fitzpatrick Jm;Wang My;Dawant Bm

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • A large annotated medical image dataset for the development and evaluation of segmentation algorithms

    Amber L. Simpson;Michela Antonelli;Spyridon Bakas;Michel Bilello

  • Perspective volume rendering of CT and MR images: applications for endoscopic imaging.

    G D Rubin;C F Beaulieu;V Argiro;H Ringl

  • Content-Based Image Retrieval in Radiology: Current Status and Future Directions

    Ceyhun Burak Akgül;Daniel L. Rubin;Sandy Napel;Christopher F. Beaulieu

  • Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches

    M. Zhou;J. Scott;B. Chaudhury;L. Hall

  • Comparison and evaluation of retrospective intermodality image registration techniques

    Jay B. West;J. Michael Fitzpatrick;Matthew Yang Wang;Benoit M. Dawant

  • Glioblastoma Multiforme: Exploratory Radiogenomic Analysis by Using Quantitative Image Features

    Olivier Gevaert;Lex A. Mitchell;Achal S. Achrol;Jiajing Xu

  • Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT

    D.S. Paik;C.F. Beaulieu;G.D. Rubin;B. Acar

  • Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection.

    Geoffrey D Rubin;John K Lyo;David S Paik;Anthony J Sherbondy

  • Characterization of spatial distortion in magnetic resonance imaging and its implications for stereotactic surgery.

    Thilaka S. Sumanaweera;John R. Adler;Sandy Napel;Gary H. Glover

  • Automated polyp detector for CT colonography: feasibility study.

    Summers Rm;Beaulieu Cf;Pusanik Lm;Malley Jd

  • Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities

    Haruka Itakura;Achal S. Achrol;Lex A. Mitchell;Joshua J. Loya

  • A radiogenomic dataset of non-small cell lung cancer

    Shaimaa Bakr;Olivier Gevaert;Sebastian Echegaray;Kelsey Ayers

  • Computed tomographic angiography: historical perspective and new state-of the-art using multi detector-row helical computed tomography

    G D Rubin;M C Shiau;A J Schmidt;D Fleischmann

  • Adaptive border marching algorithm: Automatic lung segmentation on chest CT images

    Jiantao Pu;Justus E. Roos;Chin A. Yi;Sandy Napel

  • Detection of ureteral calculi in patients with suspected renal colic: value of reformatted noncontrast helical CT.

    F G Sommer;R B Jeffrey;G D Rubin;S Napel

  • Automated flight path planning for virtual endoscopy

    David S. Paik;Christopher F. Beaulieu;R. Brooke Jeffrey;Geoffrey D. Rubin

  • A statistical 3-D pattern processing method for computer-aided detection of polyps in CT colonography

    S.B. Gokturk;C. Tomasi;B. Acar;C.F. Beaulieu

  • Phase unwrapping of MR phase images using Poisson equation

    S. Moon-Ho Song;S. Napel;N.J. Pelc;G.H. Glover

Frequent Co-Authors

Geoffrey D. Rubin
Geoffrey D. Rubin University of Arizona
Daniel L. Rubin
Daniel L. Rubin Stanford University
R B Jeffrey
R B Jeffrey Stanford University
Robert J. Gillies
Robert J. Gillies Moffitt Cancer Center
John R. Adler
John R. Adler Stanford University
Gary H. Glover
Gary H. Glover Stanford University
Michael D. Dake
Michael D. Dake University of Arizona
Carlo Tomasi
Carlo Tomasi Duke University
Salih Burak Gokturk
Salih Burak Gokturk Stanford University
Jayashree Kalpathy-Cramer
Jayashree Kalpathy-Cramer Harvard University

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