A practical model for the identification of congenital cataracts using machine learning

A practical model for the identification of congenital cataracts using machine learning

Background: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood blindness. Methods: This case-control study was pe...

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Bibliographic Details
Main Authors: Duoru Lin, Jingjing Chen, Zhuoling Lin, Xiaoyan Li, Kai Zhang, Xiaohang Wu, Zhenzhen Liu, Jialing Huang, Jing Li, Yi Zhu, Chuan Chen, Lanqin Zhao, Yifan Xiang, Chong Guo, Liming Wang, Yizhi Liu, Weirong Chen, Haotian Lin
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:EBioMedicine
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396419308369

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http://www.sciencedirect.com/science/article/pii/S2352396419308369

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