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Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms
PURPOSE: We formulated and tested ensemble learning models to classify axial length (AXL) from choroidal thickness (CT) as indicated on fovea-centered, 2D single optical coherence tomography (OCT) images. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: We analyzed 710 OCT images from 355...
Autores principales: | Lu, Hao-Chun, Chen, Hsin-Yi, Huang, Chien-Jung, Chu, Pao-Hsien, Wu, Lung-Sheng, Tsai, Chia-Ying |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273745/ https://www.ncbi.nlm.nih.gov/pubmed/35836947 http://dx.doi.org/10.3389/fmed.2022.850284 |
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