An explainable deep learning approach for automated detection and grading of diabetic retinopathy from fundus images
- DOI
- 10.1016/j.mvr.2026.105009
- Published
- 2027-01
- Container
- Microvascular Research
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.mvr.2026.105009,
title = {An explainable deep learning approach for automated detection and grading of diabetic retinopathy from fundus images},
author = {Muradul Islam and Marisa Parvez Oishy and Ferdaus Anam Jibon and Utpal Kanti Das and A.H.M. Kamal and Mohammad Mehedi Hassan and Gahangir Hossain},
year = {2027},
journal = {Microvascular Research},
doi = {10.1016/j.mvr.2026.105009},
url = {https://doi.org/10.1016/j.mvr.2026.105009}
}RIS
TY - JOUR TI - An explainable deep learning approach for automated detection and grading of diabetic retinopathy from fundus images AU - Muradul Islam AU - Marisa Parvez Oishy AU - Ferdaus Anam Jibon AU - Utpal Kanti Das AU - A.H.M. Kamal AU - Mohammad Mehedi Hassan AU - Gahangir Hossain PY - 2027 JO - Microvascular Research DO - 10.1016/j.mvr.2026.105009 UR - https://doi.org/10.1016/j.mvr.2026.105009 ER -
APA
Islam, M., Oishy, M. P., Jibon, F. A., Das, U. K., Kamal, A., Hassan, M. M., & Hossain, G. (2027). An explainable deep learning approach for automated detection and grading of diabetic retinopathy from fundus images. Microvascular Research. https://doi.org/10.1016/j.mvr.2026.105009
Source records
- crossref · retrieved 2026-09-25T17:46:31.088Z