Deep learning for dermatologists: Part I. Fundamental concepts - 30/11/22
, Pranav Puri, BA b, c, Huma Shamim, MBBS b, d, Spencer A. Bezalel, MD b, d, Lisa A. Drage, MD b, d, Michael Wang, MD e, Mark R. Pittelkow, MD b, f, Rickey E. Carter, PhD g, Mark D.P. Davis, MD b, d, Alina G. Bridges, DO b, d, h, Aaron R. Mangold, MD b, f, James A. Yiannias, MD f, Megha M. Tollefson, MD b, d, Julia S. Lehman, MD b, d, h, Alexander Meves, MD b, d, Clark C. Otley, MD b, d, Olayemi Sokumbi, MD b, i, j, Matthew R. Hall, MD b, i, Nneka Comfere, MD b, d, hAbstract |
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.
El texto completo de este artículo está disponible en PDF.Key words : artificial intelligence, deep learning, dermatology, machine learning
Abbreviations used : AI, BCC, DL, DNN, GPU, ML
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| Funding sources: None. |
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| Conflicts of interest: None disclosed. |
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| IRB approval status: Not applicable. |
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| Reprints not available from the authors. |
Vol 87 - N° 6
P. 1343-1351 - décembre 2022 Regresar al número
Artículo precedente
- Artificial intelligence in the detection of skin cancer
- Eric J. Beltrami, Alistair C. Brown, Paul J.M. Salmon, David J. Leffell, Justin M. Ko, Jane M. Grant-Kels
- Deep learning for dermatologists: Part II. Current applications
- Pranav Puri, Nneka Comfere, Lisa A. Drage, Huma Shamim, Spencer A. Bezalel, Mark R. Pittelkow, Mark D.P. Davis, Michael Wang, Aaron R. Mangold, Megha M. Tollefson, Julia S. Lehman, Alexander Meves, James A. Yiannias, Clark C. Otley, Rickey E. Carter, Olayemi Sokumbi, Matthew R. Hall, Alina G. Bridges, Dennis H. Murphree
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