224 related articles for article (PubMed ID: 30798455)
21. Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.
Ting DSW; Cheung CY; Lim G; Tan GSW; Quang ND; Gan A; Hamzah H; Garcia-Franco R; San Yeo IY; Lee SY; Wong EYM; Sabanayagam C; Baskaran M; Ibrahim F; Tan NC; Finkelstein EA; Lamoureux EL; Wong IY; Bressler NM; Sivaprasad S; Varma R; Jonas JB; He MG; Cheng CY; Cheung GCM; Aung T; Hsu W; Lee ML; Wong TY
JAMA; 2017 Dec; 318(22):2211-2223. PubMed ID: 29234807
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Diagnostic accuracy of direct ophthalmoscopy for detection of diabetic retinopathy using fundus photographs as a reference standard.
Ahsan S; Basit A; Ahmed KR; Ali L; Shaheen F; Ulhaque MS; Fawwad A
Diabetes Metab Syndr; 2014; 8(2):96-101. PubMed ID: 24907174
[TBL] [Abstract][Full Text] [Related]
24. Screening for diabetic retinopathy in rural area using single-field, digital fundus images.
Ruamviboonsuk P; Wongcumchang N; Surawongsin P; Panyawatananukul E; Tiensuwan M
J Med Assoc Thai; 2005 Feb; 88(2):176-80. PubMed ID: 15962667
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. Multi-label classification of retinal lesions in diabetic retinopathy for automatic analysis of fundus fluorescein angiography based on deep learning.
Pan X; Jin K; Cao J; Liu Z; Wu J; You K; Lu Y; Xu Y; Su Z; Jiang J; Yao K; Ye J
Graefes Arch Clin Exp Ophthalmol; 2020 Apr; 258(4):779-785. PubMed ID: 31932886
[TBL] [Abstract][Full Text] [Related]
27. The diagnosis of diabetic retinopathy. Ophthalmoscopy versus fundus photography.
Lee VS; Kingsley RM; Lee ET; Lu M; Russell D; Asal NR; Bradford RH; Wilkinson CP
Ophthalmology; 1993 Oct; 100(10):1504-12. PubMed ID: 8414411
[TBL] [Abstract][Full Text] [Related]
28. Predicting the risk of developing diabetic retinopathy using deep learning.
Bora A; Balasubramanian S; Babenko B; Virmani S; Venugopalan S; Mitani A; de Oliveira Marinho G; Cuadros J; Ruamviboonsuk P; Corrado GS; Peng L; Webster DR; Varadarajan AV; Hammel N; Liu Y; Bavishi P
Lancet Digit Health; 2021 Jan; 3(1):e10-e19. PubMed ID: 33735063
[TBL] [Abstract][Full Text] [Related]
29. Nonmydriatic ultrawide field retinal imaging compared with dilated standard 7-field 35-mm photography and retinal specialist examination for evaluation of diabetic retinopathy.
Silva PS; Cavallerano JD; Sun JK; Noble J; Aiello LM; Aiello LP
Am J Ophthalmol; 2012 Sep; 154(3):549-559.e2. PubMed ID: 22626617
[TBL] [Abstract][Full Text] [Related]
30. An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs.
Li Z; Keel S; Liu C; He Y; Meng W; Scheetz J; Lee PY; Shaw J; Ting D; Wong TY; Taylor H; Chang R; He M
Diabetes Care; 2018 Dec; 41(12):2509-2516. PubMed ID: 30275284
[TBL] [Abstract][Full Text] [Related]
31. Clinical biomicroscopy versus fluorescein angiography: effectiveness and sensitivity in detecting diabetic retinopathy.
Khalaf SS; Al-Bdour MD; Al-Till MI
Eur J Ophthalmol; 2007; 17(1):84-8. PubMed ID: 17294387
[TBL] [Abstract][Full Text] [Related]
32. The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.
Yoo TK; Choi JY; Seo JG; Ramasubramanian B; Selvaperumal S; Kim DW
Med Biol Eng Comput; 2019 Mar; 57(3):677-687. PubMed ID: 30349958
[TBL] [Abstract][Full Text] [Related]
33. Hard exudate detection based on deep model learned information and multi-feature joint representation for diabetic retinopathy screening.
Wang H; Yuan G; Zhao X; Peng L; Wang Z; He Y; Qu C; Peng Z
Comput Methods Programs Biomed; 2020 Jul; 191():105398. PubMed ID: 32092614
[TBL] [Abstract][Full Text] [Related]
34. 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]
35. Development of a Deep Learning Algorithm for Automatic Diagnosis of Diabetic Retinopathy.
Raju M; Pagidimarri V; Barreto R; Kadam A; Kasivajjala V; Aswath A
Stud Health Technol Inform; 2017; 245():559-563. PubMed ID: 29295157
[TBL] [Abstract][Full Text] [Related]
36. A deep learning system for detecting diabetic retinopathy across the disease spectrum.
Dai L; Wu L; Li H; Cai C; Wu Q; Kong H; Liu R; Wang X; Hou X; Liu Y; Long X; Wen Y; Lu L; Shen Y; Chen Y; Shen D; Yang X; Zou H; Sheng B; Jia W
Nat Commun; 2021 May; 12(1):3242. PubMed ID: 34050158
[TBL] [Abstract][Full Text] [Related]
37. Fred Hollows lecture: digital screening for eye disease.
Constable IJ; Yogesan K; Eikelboom R; Barry C; Cuypers M
Clin Exp Ophthalmol; 2000 Jun; 28(3):129-32. PubMed ID: 10981779
[TBL] [Abstract][Full Text] [Related]
38. Automatic recognition of severity level for diagnosis of diabetic retinopathy using deep visual features.
Abbas Q; Fondon I; Sarmiento A; Jiménez S; Alemany P
Med Biol Eng Comput; 2017 Nov; 55(11):1959-1974. PubMed ID: 28353133
[TBL] [Abstract][Full Text] [Related]
39. Applications of deep learning for detecting ophthalmic diseases with ultrawide-field fundus images.
Tang QQ; Yang XG; Wang HQ; Wu DW; Zhang MX
Int J Ophthalmol; 2024; 17(1):188-200. PubMed ID: 38239939
[TBL] [Abstract][Full Text] [Related]
40. Use of smartphones for detecting diabetic retinopathy: a protocol for a scoping review of diagnostic test accuracy studies.
Tan CH; Quah WH; Tan CSH; Smith H; Tudor Car L
BMJ Open; 2019 Dec; 9(12):e028811. PubMed ID: 31818832
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
