Development and Comparison of Machine Learning Algorithms to Determine Visual Field Progression Article Swipe
Osamah Saeedi
,
Michael V. Boland
,
Loris D’Acunto
,
Ramya Swamy
,
Vikram Hegde
,
Surabhi Gupta
,
Amin Venjara
,
Joby Tsai
,
Jonathan S. Myers
,
Sarah R. Wellik
,
Gustavo DeMoraes
,
Louis R. Pasquale
,
Lucy Q. Shen
,
Yangjiani Li
,
Tobias Elze
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1167/tvst.10.7.27
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1167/tvst.10.7.27
MLCs may help to determine visual field progression.
Related Topics To Compare & Contrast
Concepts
Algorithm
Artificial intelligence
Visual field
Machine learning
Computer science
Glaucoma
Pointwise
Logistic regression
Support vector machine
Random forest
Mathematics
Medicine
Ophthalmology
Mathematical analysis
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1167/tvst.10.7.27
- OA Status
- gold
- Cited By
- 14
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3177282926
All OpenAlex metadata
Raw OpenAlex JSON
No additional metadata available.