World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
4573
World Ranking
14002
National Ranking
5564

Overview

Randy Hays Moss is affiliated with Missouri University of Science and Technology in the United States. Their research spans multiple fields including Medicine and Computer Science, with specific attention to subfields such as Epidemiology, Artificial Intelligence, and Obstetrics and Gynecology.

The focus of their work prominently involves cancer research, particularly in cervical cancer and human papillomavirus (HPV). Their investigations also cover AI applications in cancer detection and treatments related to endometrial and cervical cancers.

The main topics explored in their research include:

  • Cervical Cancer and HPV Research
  • AI in cancer detection
  • Endometrial and Cervical Cancer Treatments

Their frequent co-authors are:

  • Haidar Almubarak
  • Peng Guo
  • R. Joe Stanley
  • L. Rodney Long
  • Sameer Antani

The diversity of co-authors suggests engagement with a collaborative scientific community across their areas of study.

Best Publications

  • A Methodological Approach to the Classification of Dermoscopy Images

    M. Emre Celebi;Hassan A. Kingravi;Bakhtiyar Uddin;Hitoshi Iyatomi

  • Neural network diagnosis of malignant melanoma from color images

    F. Ercal;A. Chawla;W.V. Stoecker;Hsi-Chieh Lee

  • Border detection in dermoscopy images using statistical region merging.

    M. Emre Celebi;Hassan A. Kingravi;Hitoshi Iyatomi;Y. Alp Aslandogan

  • Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes.

    Bulent Erkol;Randy Hays Moss;R. Joe Stanley;William V. Stoecker

  • Unsupervised color image segmentation: with application to skin tumor borders

    G.A. Hance;S.E. Umbaugh;R.H. Moss;W.V. Stoecker

  • Automatic detection of blue-white veil and related structures in dermoscopy images

    M. Emre Celebi;Hitoshi Iyatomi;William V. Stoecker;Randy H. Moss

  • Automatic detection of asymmetry in skin tumors.

    William V. Stoecker;William Weiling Li;Randy Hays Moss

  • A relative color approach to color discrimination for malignant melanoma detection in dermoscopy images.

    R. Joe Stanley;William V. Stoecker;Randy Hays Moss

  • Skin lesion classification using relative color features

    Yue (Iris) Cheng;Ragavendar Swamisai;Scott E. Umbaugh;Randy H. Moss

  • A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images.

    R.Joe Stanley;Randy Hays Moss;William Van Stoecker;Chetna Aggarwal

  • Detection of asymmetric blotches (asymmetric structureless areas) in dermoscopy images of malignant melanoma using relative color.

    William V. Stoecker;Kapil Gupta;R. Joe Stanley;Randy Hays Moss

  • Border detection on digitized skin tumor images

    Z. Zhang;W.V. Stoecker;R.H. Moss

  • Nuclei-Based Features for Uterine Cervical Cancer Histology Image Analysis With Fusion-Based Classification

    Peng Guo;Koyel Banerjee;R. Joe Stanley;Rodney Long

  • Automatic detection of irregular borders in melanoma and other skin tumors.

    Jeremiah Eugene Golston;William V. Stoecker;William V. Stoecker;Randy Hays Moss;Inder P. S. Dhillon

  • Detection of pigment network in dermatoscopy images using texture analysis

    Murali Anantha;Randy H. Moss;William V. Stoecker

  • An automatic color segmentation algorithm with application to identification of skin tumor borders

    Scott E. Umbaugh;Randy H. Moss;William V. Stoecker;William V. Stoecker

  • Boundary detection in skin tumor images: an overall approach and radial search algorithm

    J. E. Golston;J. E. Golston;R. H. Moss;R. H. Moss;W. V. Stoecker

  • Watershed segmentation of dermoscopy images using a watershed technique

    Hanzheng Wang;Xiaohe Chen;Randy H. Moss;R. Joe Stanley

  • Modified watershed technique and post-processing for segmentation of skin lesions in dermoscopy images

    Hanzheng Wang;Randy H. Moss;Xiaohe Chen;R. Joe Stanley

  • Editorial: digital imaging in dermatology

    William V. Stoecker;William V. Stoecker;Randy Hays Moss

Frequent Co-Authors

William V. Stoecker
William V. Stoecker Missouri University of Science and Technology
M. Emre Celebi
M. Emre Celebi University of Central Arkansas
Sameer Antani
Sameer Antani National Institutes of Health
George R. Thoma
George R. Thoma National Institutes of Health
James L. Drewniak
James L. Drewniak Missouri University of Science and Technology

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