The use of artificial intelligence (AI) for skin cancer assessment has been an emerging topic in dermatology. Leadership of dermatologists is necessary in defining how these technologies fit into clinical practice.
To characterize the evolution of AI in skin cancer assessment and characterize the involvement of dermatologists in developing these technologies.
An electronic literature search was performed using PubMed searching machine learning or artificial intelligence combined with skin cancer or melanoma. Articles were included if they used AI for screening and diagnosis of skin cancer using datasets consisting of dermatoscopic images or photographs of gross lesions.
Fifty-one articles were included, of which 41% had dermatologists included as authors. Manuscripts including dermatologists described algorithms built using more images (mean 12111 vs 660). In terms of underlying technology, AI used for skin cancer assessment has followed trends in the field of image recognition.
This review focused on models described in the medical literature and did not account for those described elsewhere.
Greater involvement of dermatologists is needed in thinking through issues in data collection, dataset biases, and applications of technology. Dermatologists can provide access to large, diverse datasets that are increasingly important for building these models.
Copyright © 2020. Published by Elsevier Inc.