Deep learning for dermatologists: Part II. Current applications

Pranav Puri, Nneka Comfere, Lisa A. Drage, Huma Shamim, Spencer A. Bezalel, Mark R. Pittelkow, Mark D.P. Davis, Michael Wang, Aaron R. Mangold, Megha M. Tollefson, Julia S. Lehman, Alexander Meves, James Andrew Yiannias, Clark C. Otley, Rickey E. Carter, Olayemi Sokumbi, Matthew R. Hall, Alina G. Bridges, Dennis H. Murphree

Research output: Contribution to journalReview article

2 Scopus citations

Abstract

Because of a convergence of the availability of large data sets, graphics-specific computer hardware, and important theoretical advancements, artificial intelligence has recently contributed to dramatic progress in medicine. One type of artificial intelligence known as deep learning has been particularly impactful for medical image analysis. Deep learning applications have shown promising results in dermatology and other specialties, including radiology, cardiology, and ophthalmology. The modern clinician will benefit from an understanding of the basic features of deep learning to effectively use new applications and to better gauge their utility and limitations. In this second article of a 2-part series, we review the existing and emerging clinical applications of deep learning in dermatology and discuss future opportunities and limitations. Part 1 of this series offered an introduction to the basic concepts of deep learning to facilitate effective communication between clinicians and technical experts.

Original languageEnglish (US)
JournalJournal of the American Academy of Dermatology
DOIs
StateAccepted/In press - 2020

Keywords

  • artificial intelligence
  • deep learning
  • dermatology
  • machine learning

ASJC Scopus subject areas

  • Dermatology

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    Puri, P., Comfere, N., Drage, L. A., Shamim, H., Bezalel, S. A., Pittelkow, M. R., Davis, M. D. P., Wang, M., Mangold, A. R., Tollefson, M. M., Lehman, J. S., Meves, A., Yiannias, J. A., Otley, C. C., Carter, R. E., Sokumbi, O., Hall, M. R., Bridges, A. G., & Murphree, D. H. (Accepted/In press). Deep learning for dermatologists: Part II. Current applications. Journal of the American Academy of Dermatology. https://doi.org/10.1016/j.jaad.2020.05.053