A deep learning fusion network trained with clinical and high-frequency ultrasound images in the multi-classification of skin diseases in comparison with dermatologists: a prospective and multicenter study

Author:

Zhu An-Qi,Wang Qiao,Shi Yi-Lei,Ren Wei-Wei,Cao Xu,Ren Tian-Tian,Wang Jing,Zhang Ya-Qin,Sun Yi-Kang,Chen Xue-Wen,Lai Yong-Xian,Ni Na,Chen Yu-Chong,Hu Jing-Liang,Mou Li-Chao,Zhao Yu-Jing,Liu Ye-Qiang,Sun Li-Ping,Zhu Xiao-XiangORCID,Xu Hui-XiongORCID,Guo Le-Hang

Publisher

Elsevier BV

Reference47 articles.

1. Prevalence of a history of skin cancer in 2007 results of an incidence-based model;Stern;Arch Dermatol,2010

2. Assessment of deep neural networks for the diagnosis of benign and malignant skin neoplasms in comparison with dermatologists: a retrospective validation study;Han;PLoS Med,2020

3. The role of imaging in the management of patients with nonmelanoma skin cancer diagnostic modalities and applications;MacFarlane;J Am Acad Dermatol,2017

4. Dermoscopy, confocal microscopy and other non-invasive tools for the diagnosis of non-melanoma skin cancers and other skin conditions;Malvehy;Acta Derm Venereol,2017

5. Common applications of dermatologic sonography;Wortsman;J Ultrasound Med,2012

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