• Albert T Young, Mulin Xiong, Jacob Pfau, Michael J Keiser, and 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.
• J. Invest. Dermatol. 2020 Aug 1; 140 (8): 1504-1512.

AbstractArtificial 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.Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

21 keywords...

hide…