Background selection schema on deep learning-based classification of dermatological disease

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成果类型：

期刊论文

作者：

Zhou, Jiancun;Wu, Zheng;Jiang, Zixi;Huang, Kai;Guo, Kehua;...

通讯作者：

Kehua Guo<&wdkj&>Shuang Zhao

作者机构：

[Guo, Kehua; Wu, Zheng; Zhou, Jiancun] Cent South Univ, Sch Comp Sci & Engn, Changsha 410083, Peoples R China.

[Zhou, Jiancun] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.

[Zhao, Shuang; Jiang, Zixi; Huang, Kai] Cent South Univ, Xiangya Hosp, Dept Dermatol, Changsha, Peoples R China.

[Zhao, Shuang; Jiang, Zixi; Huang, Kai] Cent South Univ, Xiangya Hosp, Hunan Engn Res Ctr Skin Hlth & Dis, Changsha, Peoples R China.

[Zhao, Shuang; Jiang, Zixi; Huang, Kai] Cent South Univ, Xiangya Hosp, Hunan Key Lab Skin Canc & Psoriasis, Changsha, Peoples R China.

通讯机构：

[Kehua Guo] S

[Shuang Zhao] D

School of Computer Science and Engineering, Central South University, Changsha 410083, China<&wdkj&>Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China<&wdkj&>Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China<&wdkj&>Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, China<&wdkj&>National Clinical Research Center of Geriatric Disorders, Xiangya Hospital, Central South University, China

语种：

英文

关键词：

Artificial intelligence;Deep convolutional neural network;Dermatological diseases classification;Image classification

期刊：

Computers in Biology and Medicine

ISSN：

0010-4825

年：

2022

卷：

149

页码：

105966

DOI：

10.1016/j.compbiomed.2022.105966

基金类别：

This work is supported by the Natural Science Foundation of China under Grant 62076255 and 62102147 ; Project of Intelligent Management Software for Multimodal Medical Big Data for New Generation Information Technology, Ministry of Industry and Information Technology of People’s Republic of China ( TC210804V ); Open Research Projects of Zhejiang Lab (NO. 2022RC0AB07 ); Hunan Provincial Science and Technology Plan Project (NO. 2020SK2059 ); Key technologies for extracting core data sets in medical image target detection (20A88, Key projects of Hunan Education Department); the National Science Foundation of Hunan Province under Grant 2021JJ30082 and 2022JJ30275 ; Excellent Youth Project of Hunan Provincial Education Department (NO. 21B0738 ); Yongzhou City Instructive Science and Technology Plan Project (No. 2021YZKJZD003 ); Scientific Research Projects of Hunan University of Science and Engineering (No. 20XKY054 ).

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本校为其他机构

院系归属：

信息与电子工程学院

摘要：

Skin diseases are one of the most common ailments affecting humans. Artificial intelligence based on deep learning can significantly improve the efficiency of identifying skin disorders and alleviate the scarcity of medical resources. However, the distribution of background information in dermatological datasets is imbalanced, causing generalized deep learning models to perform poorly in skin disease classification. We propose a deep learning schema that combines data preprocessing, data augmentation, and residual networks to study the influenc...

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Background selection schema on deep learning-based classification of dermatological disease

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