A Data Mining Framework for Glaucoma Decision Support Based on Optic Nerve Image Analysis Using Machine Learning Methods
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Science Applications,Health Informatics,Information Systems
Link
http://link.springer.com/article/10.1007/s41666-018-0028-7/fulltext.html
Reference88 articles.
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2. Dielemans I, de Jong PTVM, Stolk R, Vingerling JR, Grobbee DE, Hofman A (1996) Primary open-angle glaucoma, intraocular pressure, and diabetes mellitus in the general elderly population. Ophthalmology 103:1271–1275. https://doi.org/10.1016/S0161-6420(96)30511-3
3. Brandt JD (2004) Corneal thickness in glaucoma screening, diagnosis, and management. Curr Opin Ophthalmol 15:85–89
4. Prum BE, Rosenberg LF, Gedde SJ, Mansberger SL, Stein JD, Moroi SE, Herndon LW, Lim MC, Williams RD (2016) Primary Open-Angle Glaucoma Preferred Practice Pattern® guidelines. Ophthalmology 123:P41–P111. https://doi.org/10.1016/j.ophtha.2015.10.053
5. Jampel HD, Friedman D, Quigley H, Vitale S, Miller R, Knezevich F, Ding Y (2009) Agreement among glaucoma specialists in assessing progressive disc changes from photographs in open-angle glaucoma patients. Am J Ophthalmol 147:39–44.e1. https://doi.org/10.1016/j.ajo.2008.07.023
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