Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics-Reference-Cited by-同舟云学术

Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics

Published:2019-03-04 Issue:7 Volume:33 Page:1133-1139
ISSN:0950-222X
Container-title:Eye
language:en
Short-container-title:Eye

Author:

Thomas Peter B. M.^ORCID,Chan Thomas,Nixon Thomas,Muthusamy Brinda,White Andrew

Publisher

Springer Science and Business Media LLC

Subject

Ophthalmology

Link

http://www.nature.com/articles/s41433-019-0386-2.pdf

Reference20 articles.

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2. Kotecha A, et al. Developing standards for the development of glaucoma virtual clinics using a modified Delphi approach. Br J Ophthalmol. 2017;102:531–4. bjophthalmol-2017-310504

3. Drummond SR, Weir C. Chiasmal compression misdiagnosed as normal-tension glaucoma: can we avoid the pitfalls? Int Ophthalmol. 2010;30:215–9.

4. Kobayashi N, Ikeda H, Kobayashi K, Onoda T, Adachi-Usami E. [Characteristics of fifty cases of pituitary tumors in eyes diagnosed with glaucoma]. Nihon Ganka Gakkai Zasshi. 2016;120:101–9.

5. Rosenblatt F. The perceptron: a probabilistic model for information storage and organization in the brain. Psychol Rev. 1958;65:386–408.

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