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.
2. Attention-based deep learning framework for automatic fundus image processing to aid in diabetic retinopathy grading. Romero-Oraá R; Herrero-Tudela M; López MI; Hornero R; García M Comput Methods Programs Biomed; 2024 Jun; 249():108160. PubMed ID: 38583290 [TBL] [Abstract][Full Text] [Related]
3. Simple methods for the lesion detection and severity grading of diabetic retinopathy by image processing and transfer learning. Sugeno A; Ishikawa Y; Ohshima T; Muramatsu R Comput Biol Med; 2021 Oct; 137():104795. PubMed ID: 34488028 [TBL] [Abstract][Full Text] [Related]
4. Non-uniform Label Smoothing for Diabetic Retinopathy Grading from Retinal Fundus Images with Deep Neural Networks. Galdran A; Chelbi J; Kobi R; Dolz J; Lombaert H; Ben Ayed I; Chakor H Transl Vis Sci Technol; 2020 Jun; 9(2):34. PubMed ID: 32832207 [TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy. Sayres R; Taly A; Rahimy E; Blumer K; Coz D; Hammel N; Krause J; Narayanaswamy A; Rastegar Z; Wu D; Xu S; Barb S; Joseph A; Shumski M; Smith J; Sood AB; Corrado GS; Peng L; Webster DR Ophthalmology; 2019 Apr; 126(4):552-564. PubMed ID: 30553900 [TBL] [Abstract][Full Text] [Related]
8. Grading diabetic retinopathy and prostate cancer diagnostic images with deep quantum ordinal regression. Toledo-Cortés S; Useche DH; Müller H; González FA Comput Biol Med; 2022 Jun; 145():105472. PubMed ID: 35430558 [TBL] [Abstract][Full Text] [Related]
9. An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images. Papadopoulos A; Topouzis F; Delopoulos A Sci Rep; 2021 Jul; 11(1):14326. PubMed ID: 34253799 [TBL] [Abstract][Full Text] [Related]
10. 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]
11. A Multi-Label Deep Learning Model with Interpretable Grad-CAM for Diabetic Retinopathy Classification. Jiang H; Xu J; Shi R; Yang K; Zhang D; Gao M; Ma H; Qian W Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1560-1563. PubMed ID: 33018290 [TBL] [Abstract][Full Text] [Related]
12. 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]
13. Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading. Sahlsten J; Jaskari J; Kivinen J; Turunen L; Jaanio E; Hietala K; Kaski K Sci Rep; 2019 Jul; 9(1):10750. PubMed ID: 31341220 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Simultaneous Diagnosis of Severity and Features of Diabetic Retinopathy in Fundus Photography Using Deep Learning. Wang J; Bai Y; Xia B IEEE J Biomed Health Inform; 2020 Dec; 24(12):3397-3407. PubMed ID: 32750975 [TBL] [Abstract][Full Text] [Related]
16. Untangling Computer-Aided Diagnostic System for Screening Diabetic Retinopathy Based on Deep Learning Techniques. Farooq MS; Arooj A; Alroobaea R; Baqasah AM; Jabarulla MY; Singh D; Sardar R Sensors (Basel); 2022 Feb; 22(5):. PubMed ID: 35270949 [TBL] [Abstract][Full Text] [Related]
17. Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy. Tseng VS; Chen CL; Liang CM; Tai MC; Liu JT; Wu PY; Deng MS; Lee YW; Huang TY; Chen YH Transl Vis Sci Technol; 2020 Jul; 9(2):41. PubMed ID: 32855845 [TBL] [Abstract][Full Text] [Related]
18. A reliable diabetic retinopathy grading via transfer learning and ensemble learning with quadratic weighted kappa metric. Chilukoti SV; Shan L; Tida VS; Maida AS; Hei X BMC Med Inform Decis Mak; 2024 Feb; 24(1):37. PubMed ID: 38321416 [TBL] [Abstract][Full Text] [Related]
19. Joint Learning of Multi-Level Tasks for Diabetic Retinopathy Grading on Low-Resolution Fundus Images. Wang X; Xu M; Zhang J; Jiang L; Li L; He M; Wang N; Liu H; Wang Z IEEE J Biomed Health Inform; 2022 May; 26(5):2216-2227. PubMed ID: 34648460 [TBL] [Abstract][Full Text] [Related]
20. A novel approach for intelligent diagnosis and grading of diabetic retinopathy. Hai Z; Zou B; Xiao X; Peng Q; Yan J; Zhang W; Yue K Comput Biol Med; 2024 Apr; 172():108246. PubMed ID: 38471350 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]