Artificial intelligence and melanoma: A comprehensive review of clinical, dermoscopic, and histologic applications.

Journal: Pigment cell & melanoma research
Published Date:

Abstract

Melanoma detection, prognosis, and treatment represent challenging and complex areas of cutaneous oncology with considerable impact on patient outcomes and healthcare economics. Artificial intelligence (AI) applications in these tasks are rapidly developing. Neural networks with increasing levels of sophistication are being implemented in clinical image, dermoscopic image, and histopathologic specimen classification of pigmented lesions. These efforts hold promise of earlier and highly accurate melanoma detection, as well as reliable prognostication and prediction of therapeutic response. Herein, we provide a brief introduction to AI, discuss contemporary investigational applications of AI in melanoma, and summarize challenges encountered with AI.

Authors

  • Katherine M Stiff
    Department of Dermatology, MetroHealth System, Cleveland, Ohio, USA.
  • Matthew J Franklin
    Department of Dermatology, MetroHealth System, Cleveland, Ohio, USA.
  • Yufei Zhou
    School of Business, Hunan Agricultural University, Changsha 410128, China.
  • Anant Madabhushi
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.
  • Thomas J Knackstedt
    Department of Dermatology, MetroHealth System, Cleveland, Ohio, USA.