Deep learning for AI-based diagnosis of skin-related neglected tropical diseases: A pilot study.

Journal: PLoS neglected tropical diseases
PMID:

Abstract

BACKGROUND: Deep learning, which is a part of a broader concept of artificial intelligence (AI) and/or machine learning has achieved remarkable success in vision tasks. While there is growing interest in the use of this technology in diagnostic support for skin-related neglected tropical diseases (skin NTDs), there have been limited studies in this area and fewer focused on dark skin. In this study, we aimed to develop deep learning based AI models with clinical images we collected for five skin NTDs, namely, Buruli ulcer, leprosy, mycetoma, scabies, and yaws, to understand how diagnostic accuracy can or cannot be improved using different models and training patterns.

Authors

  • Rie R Yotsu
    Department of Tropical Medicine, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, Louisiana, United States of America.
  • Zhengming Ding
  • Jihun Hamm
    Department of Computer Science, Tulane University School of Science and Engineering, 201 Lindy Claiborne Boggs Center, 6823 St. Charles Avenue, New Orleans, Louisiana, United States of America.
  • Ronald E Blanton
    Department of Tropical Medicine, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, New Orleans, Louisiana, United States of America.