Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage

doi:10.1042/BSR20180497

	Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage
	Wang, Binbin 1; Xiao, Li 2; Liu, Yang 2; Wang, Jing 3; Liu, Beihong 1; Li, Tengyan 1; Ma, Xu 1; Zhao, Yi 2
	2018-12-21
发表期刊	BIOSCIENCE REPORTS
ISSN	0144-8463
卷号	38 页码:8
摘要	There is a disparity between the increasing application of digital retinal imaging to neonatal ocular screening and slowly growing number of pediatric ophthalmologists. Assistant tools that can automatically detect ocular disorders may be needed. In present study, we develop a deep convolutional neural network (DCNN) for automated classification and grading of retinal hemorrhage. We used 48,996 digital fundus images from 3770 newborns with retinal hemorrhage of different severity (grade 1, 2 and 3) and normal controls from a large cross-sectional investigation in China. The DCNN was trained for automated grading of retinal hemorrhage (multiclass classification problem: hemorrhage-free and grades 1, 2 and 3) and then validated for its performance level. The DCNN yielded an accuracy of 97.85 to 99.96%, and the area under the receiver operating characteristic curve was 0.989-1.000 in the binary classification of neonatal retinal hemorrhage (i.e., one classification vs. the others). The overall accuracy with regard to the multiclass classification problem was 97.44%. This is the first study to show that a DCNN can detect and grade neonatal retinal hemorrhage at high performance levels. Artificial intelligence will play more positive roles in ocular healthcare of newborns and children.
DOI	10.1042/BSR20180497
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2016YFC1000307] ; National Science and Technology Basic Work[2014FY130100] ; CAS Pioneer Hundred Talents Program[2017-074]
WOS研究方向	Biochemistry & Molecular Biology ; Cell Biology
WOS类目	Biochemistry & Molecular Biology ; Cell Biology
WOS记录号	WOS:000454266100019
出版者	PORTLAND PRESS LTD
引用统计	被引频次：13[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/3489
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ma, Xu; Zhao, Yi
作者单位	1.Natl Res Inst Family Planning, Ctr Genet, Beijing 100081, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Key Lab Intelligent Informat Proc,Adv Comp Res Ct, Beijing 100190, Peoples R China 3.Capital Med Univ, Sch Basic Med Sci, Dept Med Genet & Dev Biol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wang, Binbin,Xiao, Li,Liu, Yang,et al. Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage[J]. BIOSCIENCE REPORTS,2018,38:8.
APA	Wang, Binbin.,Xiao, Li.,Liu, Yang.,Wang, Jing.,Liu, Beihong.,...&Zhao, Yi.(2018).Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage.BIOSCIENCE REPORTS,38,8.
MLA	Wang, Binbin,et al."Application of a deep convolutional neural network in the diagnosis of neonatal ocular fundus hemorrhage".BIOSCIENCE REPORTS 38(2018):8.