Ensemble machine learning algorithm for anti-VEGF treatment efficacy prediction in diabetic macular edema
Abstract Background Diabetic macular edema (DME) is a leading cause of vision loss in diabetes, with variable responses to anti-vascular endothelial growth factor (anti-VEGF) therapy in DME patients. Current diagnosis relies on optical coherence tomography (OCT) imaging, but manual interpretation is...
Saved in:
| Main Authors: | Yu Fang, Jianwei Lin, Peiwen Xie, Huishan Zhu, Tsz Kin Ng, Guihua Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Ophthalmology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12886-025-04181-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Efficacy of Faricimab in the Treatment of Diabetic Macular Edema and Faricimab-Related Changes in OCT and OCT Angiography
by: Dorota Śpiewak, et al.
Published: (2025-06-01) -
Axial length and IOL power stability in macular edema treated with anti-VEGF: a preliminary study using OLCR biometry
by: Mehmet Omer Kiristioglu, et al.
Published: (2025-07-01) -
Metabolomics analysis uncovers metabolic changes and remodeling of anti-VEGF therapy on macular edema
by: Congcong Yan, et al.
Published: (2025-07-01) -
Long-Term Outcomes of Nonadherence to Anti-VEGF Therapy in Advanced Neovascular Age-Related Macular Degeneration
by: A. N. Kulikov, et al.
Published: (2022-10-01) -
A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema
by: Wenrui Lu, et al.
Published: (2025-05-01)