These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
198 related articles for article (PubMed ID: 36037631)
1. Diabetic retinopathy screening using deep learning for multi-class imbalanced datasets. Saini M; Susan S Comput Biol Med; 2022 Oct; 149():105989. PubMed ID: 36037631 [TBL] [Abstract][Full Text] [Related]
2. Identifying Diabetic Retinopathy in the Human Eye: A Hybrid Approach Based on a Computer-Aided Diagnosis System Combined with Deep Learning. Atcı ŞY; Güneş A; Zontul M; Arslan Z Tomography; 2024 Feb; 10(2):215-230. PubMed ID: 38393285 [TBL] [Abstract][Full Text] [Related]
3. IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge. Porwal P; Pachade S; Kokare M; Deshmukh G; Son J; Bae W; Liu L; Wang J; Liu X; Gao L; Wu T; Xiao J; Wang F; Yin B; Wang Y; Danala G; He L; Choi YH; Lee YC; Jung SH; Li Z; Sui X; Wu J; Li X; Zhou T; Toth J; Baran A; Kori A; Chennamsetty SS; Safwan M; Alex V; Lyu X; Cheng L; Chu Q; Li P; Ji X; Zhang S; Shen Y; Dai L; Saha O; Sathish R; Melo T; Araújo T; Harangi B; Sheng B; Fang R; Sheet D; Hajdu A; Zheng Y; Mendonça AM; Zhang S; Campilho A; Zheng B; Shen D; Giancardo L; Quellec G; Mériaudeau F Med Image Anal; 2020 Jan; 59():101561. PubMed ID: 31671320 [TBL] [Abstract][Full Text] [Related]
4. A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability. Zhou Y; Wang B; Huang L; Cui S; Shao L IEEE Trans Med Imaging; 2021 Mar; 40(3):818-828. PubMed ID: 33180722 [TBL] [Abstract][Full Text] [Related]
5. Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey. Asiri N; Hussain M; Al Adel F; Alzaidi N Artif Intell Med; 2019 Aug; 99():101701. PubMed ID: 31606116 [TBL] [Abstract][Full Text] [Related]
6. MediDRNet: Tackling category imbalance in diabetic retinopathy classification with dual-branch learning and prototypical contrastive learning. Teng S; Wang B; Yang F; Yi X; Zhang X; Sun Y Comput Methods Programs Biomed; 2024 Aug; 253():108230. PubMed ID: 38810377 [TBL] [Abstract][Full Text] [Related]
7. UC-stack: a deep learning computer automatic detection system for diabetic retinopathy classification. Fu Y; Wei Y; Chen S; Chen C; Zhou R; Li H; Qiu M; Xie J; Huang D Phys Med Biol; 2024 Feb; 69(4):. PubMed ID: 38271723 [No Abstract] [Full Text] [Related]
8. Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G. Lim WX; Chen Z Med Biol Eng Comput; 2024 Aug; 62(8):2571-2583. PubMed ID: 38649629 [TBL] [Abstract][Full Text] [Related]
9. Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning. Alyoubi WL; Abulkhair MF; Shalash WM Sensors (Basel); 2021 May; 21(11):. PubMed ID: 34073541 [TBL] [Abstract][Full Text] [Related]
11. A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique. AbdelMaksoud E; Barakat S; Elmogy M Med Biol Eng Comput; 2022 Jul; 60(7):2015-2038. PubMed ID: 35545738 [TBL] [Abstract][Full Text] [Related]
12. An Effective Method for Detecting and Classifying Diabetic Retinopathy Lesions Based on Deep Learning. Erciyas A; Barışçı N Comput Math Methods Med; 2021; 2021():9928899. PubMed ID: 34194538 [TBL] [Abstract][Full Text] [Related]
13. CauDR: A causality-inspired domain generalization framework for fundus-based diabetic retinopathy grading. Wei H; Shi P; Miao J; Zhang M; Bai G; Qiu J; Liu F; Yuan W Comput Biol Med; 2024 Jun; 175():108459. PubMed ID: 38701588 [TBL] [Abstract][Full Text] [Related]
14. Recognition of diabetic retinopathy and macular edema using deep learning. Jeribi F; Nazir T; Nawaz M; Javed A; Alhameed M; Tahir A Med Biol Eng Comput; 2024 Sep; 62(9):2687-2701. PubMed ID: 38684593 [TBL] [Abstract][Full Text] [Related]
15. Efficient multi-kernel multi-instance learning using weakly supervised and imbalanced data for diabetic retinopathy diagnosis. Cao P; Ren F; Wan C; Yang J; Zaiane O Comput Med Imaging Graph; 2018 Nov; 69():112-124. PubMed ID: 30237145 [TBL] [Abstract][Full Text] [Related]
16. Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy. Mohanty C; Mahapatra S; Acharya B; Kokkoras F; Gerogiannis VC; Karamitsos I; Kanavos A Sensors (Basel); 2023 Jun; 23(12):. PubMed ID: 37420891 [TBL] [Abstract][Full Text] [Related]
17. Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines. Nazir T; Irtaza A; Shabbir Z; Javed A; Akram U; Mahmood MT Artif Intell Med; 2019 Aug; 99():101695. PubMed ID: 31606114 [TBL] [Abstract][Full Text] [Related]
18. Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model. Nazir T; Nawaz M; Rashid J; Mahum R; Masood M; Mehmood A; Ali F; Kim J; Kwon HY; Hussain A Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450729 [TBL] [Abstract][Full Text] [Related]
19. Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions. Nadeem MW; Goh HG; Hussain M; Liew SY; Andonovic I; Khan MA Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146130 [TBL] [Abstract][Full Text] [Related]
20. Comparison review of image classification techniques for early diagnosis of diabetic retinopathy. Wangweera C; Zanini P Biomed Phys Eng Express; 2024 Sep; 10(6):. PubMed ID: 39173657 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]