Machine learning and optical coherence tomography-derived radiomics analysis to predict persistent diabetic macular edema in patients undergoing anti-VEGF intravitreal therapy

Machine learning and optical coherence tomography-derived radiomics analysis to predict persistent diabetic macular edema in patients undergoing anti-VEGF intravitreal therapy

Abstract Background Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. Methods A retrosp...

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Bibliographic Details
Main Authors: Zhishang Meng, Yanzhu Chen, Haoyu Li, Yue Zhang, Xiaoxi Yao, Yongan Meng, Wen Shi, Youling Liang, Yuqian Hu, Dan Liu, Manyun Xie, Bin Yan, Jing Luo
Format: Article
Language:English
Published: BMC 2024-04-01
Series:Journal of Translational Medicine
Subjects:
Diabetic macular edema
OCT-omics
Anti-VEGF treatment response
Retinal imaging
Prognostic model
Online Access:https://doi.org/10.1186/s12967-024-05141-7

Internet

https://doi.org/10.1186/s12967-024-05141-7

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