Radiomics Analysis Based on Optical Coherence Tomography to Prognose the Efficacy of Anti-VEGF Therapy of Retinal Vein Occlusion-Related Macular Edema
The machine learning models based on OCT technology developed here demonstrated a promising ability to prognose anti-VEGF therapeutic responses for RVO-ME. The utilization of machine learning provides a new promising approach to assessing radiomic markers in research related to RVO-ME, having a good prospect for the application of the using of precision medicine in ophthalmology.
Authors
- Jianing Qiu
- Jing Luo (ORCID: https://orcid.org/0000-0002-8905-9388)
- Zhishang Meng
- Yongan Meng (ORCID: https://orcid.org/0000-0002-0121-7426)
- Youling Liang
- Dan Liu (ORCID: https://orcid.org/0000-0001-8789-0218)
- Biying Chen (ORCID: https://orcid.org/0000-0002-9955-5684)
- Yuqian Hu (ORCID: https://orcid.org/0009-0004-3492-8306)
Institutions
- Central South University (CN)
- Hunan Provincial Center for Disease Control and Prevention (CN)
- Second Xiangya Hospital of Central South University (CN)
Publication Details
- Journal
- Investigative Ophthalmology & Visual Science
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1167/iovs.66.4.74
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08