Augmenting Kalman Filter Machine Learning Models with Data from OCT to Predict Future Visual Field Loss: An Analysis Using Data from the African Descent and Glaucoma Evaluation Study and the Diagnostic Innovation in Glaucoma Study

Zhalechian, M., Van Oyen, M. P., Lavieri, M. S., De Moraes, C. G., Girkin, C. A., Fazio, M. A., Weinreb, R. N., Bowd, C., Liebmann, J. M., Zangwill, L. M., Andrews, C. A., & Stein, J. D. (2022). Augmenting Kalman Filter Machine Learning Models with Data from OCT to Predict Future Visual Field Loss. Ophthalmology Science, 2(1), 100097. https://doi.org/10.1016/j.xops.2021.100097
Authors:
Mohammad Zhalechian
Mark P. Van Oyen
Mariel S. Lavieri
Carlos Gustavo De Moraes
Christopher A. Girkin
Massimo A. Fazio
Robert N. Weinreb
Christopher Bowd
Jeffrey M. Liebmann
Linda M. Zangwill
Christopher A. Andrews
Joshua D. Stein
Affiliated Authors:
Carlos Gustavo De Moraes
Jeffrey M. Liebmann
Columbia Affiliation:
Author Keywords:
algorithm bias
glaucoma
kalman filter
machine learning
oct
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Publication Type:
Article
Unique ID:
10.1016/j.xops.2021.100097
DOI:
10.1016/j.xops.2021.100097
Journal:
Ophthalmology Science
Publication Date:
Data Source:
Scopus
Source Link:
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