Development of a deep residual learning algorithm to screen for glaucoma from fundus photography

The Purpose of the study was to develop a deep residual learning algorithm to screen for glaucoma from fundus photography and measure its diagnostic performance compared to Residents in Ophthalmology. A training dataset consisted of 1,364 color fundus photographs with glaucomatous indications and 1,...

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Veröffentlicht in:	Scientific reports 2018-10, Vol.8 (1), p.14665-9, Article 14665
Hauptverfasser:	Shibata, Naoto, Tanito, Masaki, Mitsuhashi, Keita, Fujino, Yuri, Matsuura, Masato, Murata, Hiroshi, Asaoka, Ryo
Format:	Artikel
Sprache:	eng
Schlagworte:	692/308 692/308/575 Algorithms Color Datasets Glaucoma Humanities and Social Sciences multidisciplinary Photography Science Science (multidisciplinary) Training Weights & measures
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