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Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification
OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior capsule opacification (PCO) and to discriminate between clinically significant and non-significant PCOs. METHODS AND ANALYSIS: For this retrospective...
Autores principales: | Huemer, Josef, Kronschläger, Martin, Ruiss, Manuel, Sim, Dawn, Keane, Pearse A, Findl, Oliver, Wagner, Siegfried K |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9174773/ https://www.ncbi.nlm.nih.gov/pubmed/36161827 http://dx.doi.org/10.1136/bmjophth-2022-000992 |
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