How I learned to stop worrying and love machine learning.

Journal: Clinics in dermatology
Published Date: Jan 1, 2018

Abstract

Artificial intelligence and its machine learning (ML) capabilities are very promising technologies for dermatology and other visually oriented fields due to their power in pattern recognition. Understandably, many physicians distrust replacing clinical finesse with unsupervised computer programs. We describe convolutional neural networks and discuss how this method of ML will impact the field of dermatology. ML is a form of artificial intelligence well suited for pattern recognition in visual applications. Many dermatologists are wary of such unsupervised algorithms and their future implications.

Authors

  • Sarah Mattessich
    University of Connecticut School of Medicine, Farmington, Connecticut, USA.
  • Michael Tassavor
    Department of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
  • Susan M Swetter
    Department of Dermatology, Stanford University, Stanford, California, USA.
  • Jane M Grant-Kels
    Department of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut.

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