| Literature DB >> 32434009 |
Dennis H Murphree1, Pranav Puri2, Huma Shamim3, Spencer A Bezalel3, Lisa A Drage3, Michael Wang4, Mark R Pittelkow5, Rickey E Carter6, Mark D P Davis3, Alina G Bridges7, Aaron R Mangold5, James A Yiannias8, Megha M Tollefson3, Julia S Lehman7, Alexander Meves3, Clark C Otley3, Olayemi Sokumbi9, Matthew R Hall10, Nneka Comfere7.
Abstract
Artificial intelligence is generating substantial interest in the field of medicine. One form of artificial intelligence, deep learning, has led to rapid advances in automated image analysis. In 2017, an algorithm demonstrated the ability to diagnose certain skin cancers from clinical photographs with the accuracy of an expert dermatologist. Subsequently, deep learning has been applied to a range of dermatology applications. Although experts will never be replaced by artificial intelligence, it will certainly affect the specialty of dermatology. In this first article of a 2-part series, the basic concepts of deep learning will be reviewed with the goal of laying the groundwork for effective communication between clinicians and technical colleagues. In part 2 of the series, the clinical applications of deep learning in dermatology will be reviewed and limitations and opportunities will be considered.Entities:
Keywords: artificial intelligence; deep learning; dermatology; machine learning
Year: 2020 PMID: 32434009 PMCID: PMC7669702 DOI: 10.1016/j.jaad.2020.05.056
Source DB: PubMed Journal: J Am Acad Dermatol ISSN: 0190-9622 Impact factor: 11.527