MediDRNet: Tackling category imbalance in diabetic retinopathy classification with dual-branch learning and prototypical contrastive learning-Reference-Cited by-同舟云学术

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MediDRNet: Tackling category imbalance in diabetic retinopathy classification with dual-branch learning and prototypical contrastive learning

Published:2024-08 Issue: Volume:253 Page:108230
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Teng Siying^ORCID,Wang Bo,Yang Feiyang^ORCID,Yi Xingcheng,Zhang Xinmin^ORCID,Sun Yabin

Publisher

Elsevier BV

Reference44 articles.

1. Diabetic retinopathy-ocular complications of diabetes mellitus;Nentwich;World J. Diabetes,2015

2. Diabetic retinopathy: Looking forward to 2030;Tan;Front. Endocrinol.,2023

3. Survey on diagnosis of diseases from retinal images;Das,2018

4. N. Silberman, K. Ahrlich, R. Fergus, L. Subramanian, Case for automated detection of diabetic retinopathy, in: 2010 AAAI Spring Symposium Series, 2010.

5. Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools;Ranjbarzadeh;Comput. Biol. Med.,2023

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