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Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study

PURPOSE: Machine-learning classifiers are trained computerized systems with the ability to detect the relationship between multiple input parameters and a diagnosis. The present study investigated whether the use of machine-learning classifiers improves optical coherence tomography (OCT) glaucoma de...

Täydet tiedot

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Bibliografiset tiedot
Päätekijät: Burgansky-Eliash, Zvia, Wollstein, Gadi, Chu, Tianjiao, Ramsey, Joseph D., Glymour, Clark, Noecker, Robert J., Ishikawa, Hiroshi, Schuman, Joel S.
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: 2005
Aiheet:
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC1941765/
https://ncbi.nlm.nih.gov/pubmed/16249492
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/iovs.05-0366
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