Department of Dermatology, Temple University Lewis Katz School of Medicine, Philadelphia, Pennsylvania, USA.
Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
Clin Dermatol. 2021 Jul-Aug;39(4):667-672. doi: 10.1016/j.clindermatol.2021.03.012. Epub 2021 Mar 19.
As medicine enters the era of artificial intelligence (AI)-augmented practice, dermatology is beginning to witness the integration of AI into the daily practice, particularly in the areas of diagnosis, prognosis, and treatment of skin diseases. Many of the current electronic medical records that dermatologists have incorporated provide guidance in billing, a form of AI at work. The recent advances in visual recognition AI make application and integration of the technology particularly suited for perceptual specialties such as radiology and dermatology. In dermatology, AI is poised to improve the efficiency and accuracy of traditional diagnostic approaches, including visual examination, skin biopsy, and histopathologic examination. This review highlights the current progress of AI in dermatology and provides a basic overview of the technology.
随着医学进入人工智能（AI）增强实践的时代，皮肤病学开始见证 AI 融入日常实践，特别是在皮肤病的诊断、预后和治疗领域。皮肤科医生目前整合的许多电子病历都为计费提供了指导，这是 AI 的一种应用形式。最近在视觉识别 AI 方面的进展使得该技术尤其适用于放射学和皮肤病学等感知专业。在皮肤病学中，AI 有望提高传统诊断方法（包括视觉检查、皮肤活检和组织病理学检查）的效率和准确性。本综述重点介绍了 AI 在皮肤病学中的最新进展，并提供了该技术的基本概述。
