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Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome

文献类型：期刊论文

作者Pan, Zhouxian7; Shen, Zhen2,3; Zhu, Huijuan4; Bao, Yin2,5; Liang, Siyu4; Wang, Shirui4; Li, Xiangying4; Niu, Lulu2,6; Dong, Xisong2; Shang, Xiuqin2
刊名ENDOCRINE
出版日期2020-11-10
页码9
关键词Facial pattern recognition Turner syndrome Deep convolutional neural network Prospective study
ISSN号1355-008X
DOI10.1007/s12020-020-02539-3
通讯作者Chen, Shi(cspumch@163.com) ; Pan, Hui(panhui20111111@163.com) ; Xiong, Gang(gang.xiong@ia.ac.cn)
英文摘要Purpose Automated facial recognition technology based on deep learning has achieved high accuracy in diagnosing various endocrine diseases and genetic syndromes. This study attempts to establish a facial diagnostic system for Turner syndrome (TS) based on deep convolutional neural networks. Methods Photographs of 207 TS patients and 1074 female controls were collected from July 2016 to April 2019. Finally, 170 patients diagnosed with TS and 1053 female controls were included. Deep convolutional neural networks were used to develop the facial diagnostic system. A prospective study, which included two TS patients and 35 controls, was conducted to test the efficacy in the real clinical setting. Results The average areas under the curve (AUCs) in three different scenarios were 0.9540 +/- 0.0223, 0.9662 +/- 0.0108 and 0.9557 +/- 0.0119, separately. The average sensitivity and specificity of the prospective study were 96.7% and 97.0%, respectively. Conclusions The facial diagnostic system achieved high accuracy. Prospective study results demonstrated the application value of this system, which is promising in the screening of Turner syndrome.
WOS关键词AGE ; FEATURES
资助项目Beijing Municipal Natural Science Foundation[7192153] ; National Natural Science Foundation of China[61773382] ; National Natural Science Foundation of China[U190920015] ; National Natural Science Foundation of China[61773381] ; CAMS Initiative for Innovative Medicine[2016-I2M-1-008] ; CAS Key Technology Talent Program
WOS研究方向Endocrinology & Metabolism
语种英语
WOS记录号WOS:000588275600001
出版者SPRINGER
资助机构Beijing Municipal Natural Science Foundation ; National Natural Science Foundation of China ; CAMS Initiative for Innovative Medicine ; CAS Key Technology Talent Program
源URL[http://ir.ia.ac.cn/handle/173211/41730]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Chen, Shi; Pan, Hui; Xiong, Gang
作者单位1.Chinese Acad Sci, Cloud Comp Ctr, Guangdong Engn Res Ctr 3D Printing & Intelligent, Dongguan 523808, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
4.CAMS & PUMC, PUMCH, Minist Hlth, Dept Endocrinol,Endocrine Key Lab, Beijing 100730, Peoples R China
5.Univ Southampton, Sch Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
7.Chinese Acad Med Sci & Peking Union Med Coll CAMS, Peking Union Med Coll Hosp PUMCH, Dept Allergy, Beijing 100730, Peoples R China
推荐引用方式
GB/T 7714		 Pan, Zhouxian,Shen, Zhen,Zhu, Huijuan,et al. Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome[J]. ENDOCRINE,2020:9.
APA Pan, Zhouxian.,Shen, Zhen.,Zhu, Huijuan.,Bao, Yin.,Liang, Siyu.,...&Xiong, Gang.(2020).Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome.ENDOCRINE,9.
MLA Pan, Zhouxian,et al."Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome".ENDOCRINE (2020):9.

入库方式： OAI收割

来源：自动化研究所

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