Deep learning for automated glaucomatous optic neuropathy detection from ultra-widefield fundus images

Background/AimsTo develop a deep learning system for automated glaucomatous optic neuropathy (GON) detection using ultra-widefield fundus (UWF) images.MethodsWe trained, validated and externally evaluated a deep learning system for GON detection based on 22 972 UWF images from 10 590 subjects that w...

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Veröffentlicht in:	British journal of ophthalmology 2021-11, Vol.105 (11), p.1548-1554
Hauptverfasser:	Li, Zhongwen, Guo, Chong, Lin, Duoru, Nie, Danyao, Zhu, Yi, Chen, Chuan, Zhao, Lanqin, Wang, Jinghui, Zhang, Xulin, Dongye, Meimei, Wang, Dongni, Xu, Fabao, Jin, Chenjin, Zhang, Ping, Han, Yu, Yan, Pisong, Han, Ying, Lin, Haotian
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Automation Classification Clinical science Datasets Deep Learning Diagnostic tests/Investigation Fundus Oculi Glaucoma Glaucoma - diagnosis Humans Imaging Medical diagnosis Medical personnel Medical screening Optic Disk Optic Nerve Diseases - diagnosis Outpatient care facilities Performance evaluation ROC Curve
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