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

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Use this link to cite this item : https://ir.lib.shimane-u.ac.jp/53111

language	eng
Author	Shibata Naoto Queue inc, Tokyo, Japan TANITO, Masaki Mitsuhashi Keita Queue inc, Tokyo, Japan Fujino Yuri Department of Ophthalmology, The University of Tokyo, Tokyo, Japan Department of Ophthalmology, Graduate School of Medical Science, Kitasato University, Sagamihara Kanagawa, Japan Matsuura Masato Department of Ophthalmology, The University of Tokyo, Tokyo, Japan Department of Ophthalmology, Graduate School of Medical Science, Kitasato University, Sagamihara Kanagawa, Japan Murata Hiroshi Department of Ophthalmology, The University of Tokyo, Tokyo, Japan Asaoka Ryo Department of Ophthalmology, The University of Tokyo, Tokyo, Japan
Journal Title	SCIENTIFIC REPORTS
Volume	8
ISSN	2045-2322
Published Date	2018-10-2
DOI	10.1038/s41598-018-33013-w
PubMed ID	30279554
Publisher	NATURE PUBLISHING GROUP
NII Type	Journal Article
OAI-PMH Set	Faculty of Medicine
Remark	Supported by Grant 17K11418 from the Ministry of Education, Culture, Sports, Science and Technology of Japan and the Translational Research program; Strategic PRomotion for practical application of INnovative medical Technology, TR-SPRINT, from Japan Agency for Medical Research and Development, AMED. This research is (partially) supported by The Translational Research program; Strategic PRomotion for practical application of INnovative medical Technology, TR-SPRINT, from Japan Agency for Medical Research and Development, AMED, Grant 17K11418 from the Ministry of Education, Culture, Sports, Science, and Technology of Japan and Japan Science and Technology Agency (JST) CREST JPMJCR1304.