Artificial Intelligence in Dermatology: A Primer.

Journal: The Journal of investigative dermatology
Published Date:

Abstract

Artificial intelligence is becoming increasingly important in dermatology, with studies reporting accuracy matching or exceeding dermatologists for the diagnosis of skin lesions from clinical and dermoscopic images. However, real-world clinical validation is currently lacking. We review dermatological applications of deep learning, the leading artificial intelligence technology for image analysis, and discuss its current capabilities, potential failure modes, and challenges surrounding performance assessment and interpretability. We address the following three primary applications: (i) teledermatology, including triage for referral to dermatologists; (ii) augmenting clinical assessment during face-to-face visits; and (iii) dermatopathology. We discuss equity and ethical issues related to future clinical adoption and recommend specific standardization of metrics for reporting model performance.

Authors

  • Albert T Young
    Department of Dermatology, Henry Ford Hospital, Detroit, Michigan.
  • Mulin Xiong
    Michigan State University College of Human Medicine, East Lansing, Michigan, USA.
  • Jacob Pfau
    Department of Dermatology, University of California, San Francisco, San Francisco, California, USA; Dermatology Service, San Francisco Veterans Affairs Medical Center, San Francisco, California, USA.
  • Michael J Keiser
    Department of Pharmaceutical Chemistry, Department of Bioengineering and Therapeutic Sciences, Institute for Neurodegenerative Diseases and Bakar Institute for Computational Health Sciences , University of California-San Francisco , 675 Nelson Rising Lane , San Francisco , California 94158 , United States.
  • Maria L Wei
    Department of Dermatology, University of California, San Francisco, San Francisco, California, USA; Dermatology Service, San Francisco Veterans Affairs Medical Center, San Francisco, California, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, USA. Electronic address: maria.wei@ucsf.edu.