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Machine learning helps improve diagnostic ability of subclinical keratoconus using Scheimpflug and OCT imaging modalities
PURPOSE: To develop an automated classification system using a machine learning classifier to distinguish clinically unaffected eyes in patients with keratoconus from a normal control population based on a combination of Scheimpflug camera images and ultra-high-resolution optical coherence tomograph...
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| Publicat a: | Eye Vis (Lond) |
|---|---|
| Autors principals: | , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7507244/ https://ncbi.nlm.nih.gov/pubmed/32974414 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40662-020-00213-3 |
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