Deep learning for dermatologists: Part I. Fundamental concepts.
Deep learning for dermatologists: Part I. Fundamental concepts.
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DOI：
10.1016/j.jaad.2020.05.056
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发表时间：
2022-12
影响因子：
13.8
通讯作者：
Comfere N
中科院分区：
文献类型：
--
作者：
Murphree DH;Puri P;Shamim H;Bezalel SA;Drage LA;Wang M;Pittelkow MR;Carter RE;Davis MDP;Bridges AG;Mangold AR;Yiannias JA;Tollefson MM;Lehman JS;Meves A;Otley CC;Sokumbi O;Hall MR;Comfere N
人工智能(AI)在医学领域引起了极大的兴趣。人工智能的一种形式，深度学习，导致了自动图像分析的快速发展。2017年，一种算法展示了从临床照片诊断某些皮肤癌的能力，其准确度达到皮肤科专家的水平。随后，深度学习被应用到皮肤科的一系列应用中。虽然专家永远不会被人工智能取代，但它肯定会影响皮肤科的专业。在这两部分系列的第一篇文章中，将回顾深度学习的基本概念，目的是为临床医生和技术同事之间的有效沟通奠定基础。在本系列的第二部分，将回顾深度学习在皮肤科的临床应用，考虑到局限性和机会。
Artificial intelligence (AI) 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. Though experts will never be replaced by AI, it will certainly impact the specialty of dermatology. In this first article of a two-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 two of the series, the clinical applications of deep learning in dermatology will be reviewed considering limitations and opportunities.
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作者：
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通讯作者：
Abadi, Martin