World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
16521
World Ranking
3041
National Ranking
1488

Sameer Antani 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 Sameer Antani 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: 347 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Sameer Antani 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 Sameer Antani 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: 61 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Sameer Antani is affiliated with the National Institutes of Health in the United States. Their research spans multiple disciplines, primarily focusing on medicine and computer science, with a significant emphasis on radiology, artificial intelligence, and computer vision. Antani's work contributes to applied areas such as epidemiology and oncology, reflecting a broad engagement with medical imaging and diagnostic technologies.

Antani's publication record includes contributions to a range of journals and conference proceedings, with frequent appearances in venues such as:

  • arXiv (Cornell University)
  • Diagnostics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • IEEE Access
  • PLoS ONE

The scientist has engaged in research addressing diverse topics, including:

  • COVID-19 diagnosis using AI
  • AI in cancer detection
  • Radiomics and machine learning in medical imaging
  • Cervical cancer and HPV research
  • Infectious diseases and tuberculosis
  • Digital imaging for blood diseases
  • Lung cancer diagnosis and treatment

Antani has co-authored extensively with several researchers, including Sivaramakrishnan Rajaraman, Zhiyun Xue, Ghada Zamzmi, L. Rodney Long, and Mark Schiffman. These collaborations indicate a focus on interdisciplinary approaches combining medical expertise with advanced computational techniques.

Among the recent notable papers by Antani are:

  • Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-Rays (2020, PubMed Central)
  • Modality-Specific Deep Learning Model Ensembles Toward Improving TB Detection in Chest Radiographs (2020, IEEE Access)
  • Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification (2020, Medical Image Analysis)
  • Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears (2020, IEEE Journal of Biomedical and Health Informatics)
  • Weakly Labeled Data Augmentation for Deep Learning: A Study on COVID-19 Detection in Chest X-Rays (2020, Diagnostics)

In addition to journal articles, Antani has authored a book titled Medical Image Learning with Limited and Noisy Data, published in 2022 by Springer Science+Business Media. This work addresses challenges in medical image analysis under constraints of limited and imperfect data.

Best Publications

  • Preparing a collection of radiology examinations for distribution and retrieval

    Dina Demner-Fushman;Marc D. Kohli;Marc B. Rosenman;Sonya E. Shooshan

  • Two public chest X-ray datasets for computer-aided screening of pulmonary diseases.

    Stefan Jaeger;Sema Candemir;Sameer Antani;Yì-Xiáng J. Wáng

  • Automatic Tuberculosis Screening Using Chest Radiographs

    Stefan Jaeger;Alexandros Karargyris;Sema Candemir;Les Folio

  • Lung Segmentation in Chest Radiographs Using Anatomical Atlases With Nonrigid Registration

    Sema Candemir;Stefan Jaeger;Kannappan Palaniappan;Jonathan P. Musco

  • A survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video

    Sameer K. Antani;Rangachar Kasturi;Ramesh C. Jain

  • Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images

    Sivaramakrishnan Rajaraman;Sameer K. Antani;Mahdieh Poostchi;Kamolrat Silamut

  • Histology image analysis for carcinoma detection and grading

    Lei He;L. Rodney Long;Sameer Antani;George R. Thoma

  • An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening.

    Liming Hu;David Bell;Sameer Antani;Zhiyun Xue

  • Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-Rays

    Sivaramakrishnan Rajaraman;Jenifer Siegelman;Philip O. Alderson;Lucas S. Folio

  • CNN-based image analysis for malaria diagnosis

    Zhaohui Liang;Andrew Powell;Ilker Ersoy;Mahdieh Poostchi

  • Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs.

    Sivaramakrishnan Rajaraman;Sema Candemir;Incheol Kim;George Thoma

  • Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears

    Feng Yang;Mahdieh Poostchi;Hang Yu;Zhou Zhou

  • Multimodal Recurrent Model with Attention for Automated Radiology Report Generation

    Yuan Xue;Tao Xu;L. Rodney Long;Zhiyun Xue

  • Ontology of gaps in content-based image retrieval.

    Thomas Martin Deserno;Thomas Martin Deserno;Sameer K. Antani;L. Rodney Long

  • Evaluating performance of biomedical image retrieval systems--an overview of the medical image retrieval task at ImageCLEF 2004-2013.

    Jayashree Kalpathy-Cramer;Alba Garcia Seco de Herrera;Dina Demner-Fushman;Sameer K. Antani

  • A Learning-Based Similarity Fusion and Filtering Approach for Biomedical Image Retrieval Using SVM Classification and Relevance Feedback

    M. Rahman;S. Antani;G. Thoma

  • Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images

    Sivaramakrishnan Rajaraman;Stefan Jaeger;Sameer K Antani

  • How far have we come? Artificial intelligence for chest radiograph interpretation.

    K Kallianos;J Mongan;Sameer Antani;T Henry

  • Overview of the ImageCLEF 2013 medical tasks

    Alba Garcia Seco de Herrera;Jayashree Kalpathy-Cramer;Dina Demner-Fushman;Sameer K. Antani

  • Feature Selection for Automatic Tuberculosis Screening in Frontal Chest Radiographs.

    Szilárd Vajda;Alexandros Karargyris;Stefan Jaeger;K.C. Santosh

  • The accuracy of colposcopic grading for detection of high-grade cervical intraepithelial neoplasia

    L. Stewart Massad;L. Stewart Massad;Jose Jeronimo;Hormuzd A. Katki;Mark Schiffman

Frequent Co-Authors

George R. Thoma
George R. Thoma National Institutes of Health
Dina Demner-Fushman
Dina Demner-Fushman National Institutes of Health
Xiaolei Huang
Xiaolei Huang Pennsylvania State University
Mark Schiffman
Mark Schiffman National Institutes of Health
Rangachar Kasturi
Rangachar Kasturi University of South Florida
William V. Stoecker
William V. Stoecker Missouri University of Science and Technology
Henning Müller
Henning Müller University of Applied Sciences and Arts Western Switzerland
Yuan Xue
Yuan Xue The Ohio State University
Jayashree Kalpathy-Cramer
Jayashree Kalpathy-Cramer Harvard University
Clement J. McDonald
Clement J. McDonald National Institutes of Health

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