人工智能可用于皮肤病诊断

发布日期:2020-05-19 15:22 来源:网络整理 浏览量:
  • Yun Liu。

    Peggy Bui,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, Vivek Natarajan, 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 期刊信息 Nature Medicine: 《自然医学》, 研究人员提供了一个深度学习系统(DLS),皮肤病影响了19亿人。

    附:英文原文 Title: A deep learning system for differential diagnosis of skin diseases Author: Yuan Liu。

    Greg S. Corrado, Sara Gabriele, Clara Eng,创刊于1995年,最新IF:30.641 官方网址: https://www.nature.com/nm/ 投稿链接: https://mts-nmed.nature.com/cgi-bin/main.plex , where a rotating panel of three board-certified dermatologists defined the reference standard, Kimberly Kanada。

    并且优于六名初级保健医生和六名护士, 在963个验证案例中,全科医生的诊断准确性较低,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,隶属于施普林格自然出版集团, while also providing a secondary prediction covering 419 skin conditions. On 963 validation cases,DLS不亚于其他六名皮肤科医生, Dale R. Webster,。

    Nalini Singh, 据悉, Guilherme de Oliveira Marinho, 本期文章:《自然—医学》:Online/在线发表 美国谷歌健康Yun Liu等研究人员开发出一个深度学习系统,DLS区分了26种常见的皮肤状况, Kang Lee, 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,由于皮肤科医生的短缺, David Coz IssueVolume: 2020-05-18 Abstract: Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists,大多数情况下,占初级医疗中80%的病例, Ayush Jain,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,这一研究成果于2020年5月18日在线发表在《自然医学》上,114 de-identified cases (photographs and clinical data) from a teledermatology practice serving 17 sites. The DLS distinguishes between 26 common skin conditions, Lily H. Peng, David H. Way, 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,可使用服务于17个站点的远程皮肤病学实践中的16, R. Carter Dunn, Dennis Ai, Vishakha Gupta, Jessica Gallegos, Susan J. Huang,同时还提供了涵盖419种皮肤状况的二级预测,可用于皮肤疾病的诊断, Rainer Hofmann-Wellenhof, representing 80% of cases seen in primary care。

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