Unsupervised Machine Learning with Independent Component Analysis to Identify Areas of Progression in Glaucomatous Visual Fields-Reference-Cited by-同舟云学术

Unsupervised Machine Learning with Independent Component Analysis to Identify Areas of Progression in Glaucomatous Visual Fields

Published:2005-10-01 Issue:10 Volume:46 Page:3684
ISSN:1552-5783
Container-title:Investigative Opthalmology & Visual Science
language:en
Short-container-title:Invest. Ophthalmol. Vis. Sci.

Author:

Sample Pamela A.¹,Boden Catherine¹,Zhang Zuohua²,Pascual John¹,Lee Te-Won³,Zangwill Linda M.⁴,Weinreb Robert N.⁴,Crowston Jonathan G.⁴,Hoffmann Esther M.⁴,Medeiros Felipe A.⁴,Sejnowski Terrence⁵,Goldbaum Michael⁶

Affiliation:

1. From the Visual Function and

2. Ophthalmic Informatics Laboratories, the3Institute for Neural Computation, Department of Ophthalmology, University of California, San Diego, La Jolla, California; and

3. Institute for Neural Computation, Department of Ophthalmology, University of California, San Diego, La Jolla, California; and

4. Hamilton Glaucoma Center, and the

5. The Salk Institute, La Jolla, California.

6. Ophthalmic Informatics Laboratories, the

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Subject

General Medicine

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