A Novel Transformer Model With Multiple Instance Learning for Diabetic Retinopathy Classification
Author:
Affiliation:
1. College of Science, China Jiliang University, Hangzhou, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10384372.pdf?arnumber=10384372
Reference38 articles.
1. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045
2. Automatic Detection of Diabetic Eye Disease Through Deep Learning Using Fundus Images: A Survey
3. Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey
4. Deep Learning–Based Algorithms in Screening of Diabetic Retinopathy: A Systematic Review of Diagnostic Performance
5. An image is worth 16 × 16 words: Transformers for image recognition at scale;Dosovitskiy;arXiv:2010.11929,2020
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. SwAV-driven diagnostics: new perspectives on grading diabetic retinopathy from retinal photography;Frontiers in Robotics and AI;2024-09-13
2. Diabetic retinopathy detection using supervised and unsupervised deep learning: a review study;Artificial Intelligence Review;2024-05-02
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