OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning
Abstract Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. To address the issue, this study uses opti...
Saved in:
Main Authors: | Md Mahmudul Hasan, Jack Phu, Henrietta Wang, Arcot Sowmya, Michael Kalloniatis, Erik Meijering |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-87219-w |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comparison of glaucoma progression rate in glaucoma patients at different stages using guided progression analysis with optical coherence tomography
by: Okan Akmaz, et al.
Published: (2025-01-01) -
Comparing structural and vascular parameters between advanced pseudoexfoliation glaucoma and primary open angle glaucoma using optical coherence tomography angiography
by: Yadollah Eslami, et al.
Published: (2025-01-01) -
Evaluation of macula ganglion cell analysis and retinal nerve fiber layer thickness in preperimetric glaucoma, early stage glaucoma and healthy individuals
by: Ozlem AKTAS OZALTUN, et al.
Published: (2025-04-01) -
Structural reversal of disc cupping measured in Bruch’s membrane opening-based OCT morphometry after PRESERFLO microshunt implantation for open-angle glaucoma
by: Jan Niklas Lüke, et al.
Published: (2025-01-01) -
Macular Optical Coherence Tomography Imaging in Glaucoma
by: Alireza Kamalipour, et al.
Published: (2021-07-01)