An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis-Reference-Cited by-同舟云学术

An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis

Published:2019-01-25 Issue:1 Volume:60 Page:365
ISSN:1552-5783
Container-title:Investigative Opthalmology & Visual Science
language:en
Short-container-title:Invest. Ophthalmol. Vis. Sci.

Author:

Wang Mengyu¹,Shen Lucy Q.²,Pasquale Louis R.²³,Petrakos Paul²,Formica Sydney²,Boland Michael V.⁴,Wellik Sarah R.⁵,De Moraes Carlos Gustavo⁶,Myers Jonathan S.⁷,Saeedi Osamah⁸,Wang Hui¹⁹,Baniasadi Neda¹,Li Dian¹,Tichelaar Jorryt¹,Bex Peter J.¹⁰,Elze Tobias¹¹¹

Affiliation:

1. Schepens Eye Research Institute, Harvard Medical School, Boston, Massachusetts, United States

2. Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States

3. Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States

4. Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States

5. Bascom Palmer Eye Institute, University of Miami School of Medicine, Miami, Florida, United States

6. Edward S. Harkness Eye Institute, Columbia University Medical Center, New York, New York, United States

7. Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania, United States

8. Department of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, Maryland, United States

9. Institute for Psychology and Behavior, Jilin University of Finance and Economics, Changchun, China

10. Department of Psychology, Northeastern University, Boston, Massachusetts, United States

11. Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Subject

General Medicine

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