小柯机器人

人工智能可用于皮肤病诊断
2020-05-19 13:25

美国谷歌健康Yun Liu等研究人员开发出一个深度学习系统,可用于皮肤疾病的诊断。这一研究成果于2020年5月18日在线发表在《自然—医学》上。

研究人员提供了一个深度学习系统(DLS),可使用服务于17个站点的远程皮肤病学实践中的16,114例去识别病例(照片和临床数据)来提供皮肤状况的鉴别诊断。DLS区分了26种常见的皮肤状况,占初级医疗中80%的病例,同时还提供了涵盖419种皮肤状况的二级预测。
 
在963个验证案例中,由三名获得认证的皮肤科医生组成的小组确定了参考标准,DLS不亚于其他六名皮肤科医生,并且优于六名初级保健医生和六名护士。这些结果突出了DLS在协助全科医生诊断皮肤状况方面的潜力。
 
据悉,皮肤病影响了19亿人。由于皮肤科医生的短缺,大多数情况下,全科医生的诊断准确性较低。
 
附:英文原文

Title: A deep learning system for differential diagnosis of skin diseases

Author: Yuan Liu, Ayush Jain, Clara Eng, David H. Way, Kang Lee, Peggy Bui, Kimberly Kanada, Guilherme de Oliveira Marinho, Jessica Gallegos, Sara Gabriele, Vishakha Gupta, Nalini Singh, Vivek Natarajan, Rainer Hofmann-Wellenhof, Greg S. Corrado, Lily H. Peng, Dale R. Webster, Dennis Ai, Susan J. Huang, Yun Liu, R. Carter Dunn, David Coz

Issue&Volume: 2020-05-18

Abstract: Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of skin conditions using 16,114 de-identified cases (photographs and clinical data) from a teledermatology practice serving 17 sites. The DLS distinguishes between 26 common skin conditions, representing 80% of cases seen in primary care, while also providing a secondary prediction covering 419 skin conditions. On 963 validation cases, where a rotating panel of three board-certified dermatologists defined the reference standard, the DLS was non-inferior to six other dermatologists and superior to six primary care physicians (PCPs) and six nurse practitioners (NPs) (top-1 accuracy: 0.66 DLS, 0.63 dermatologists, 0.44 PCPs and 0.40 NPs). These results highlight the potential of the DLS to assist general practitioners in diagnosing skin conditions.

DOI: 10.1038/s41591-020-0842-3

Source: https://www.nature.com/articles/s41591-020-0842-3

Nature Medicine:《自然—医学》,创刊于1995年。隶属于施普林格·自然出版集团,最新IF:87.241
官方网址:https://www.nature.com/nm/
投稿链接:https://mts-nmed.nature.com/cgi-bin/main.plex


本期文章:《自然—医学》:Online/在线发表

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