217 related articles for article (PubMed ID: 34901058)
1. Screening Referable Diabetic Retinopathy Using a Semi-automated Deep Learning Algorithm Assisted Approach.
Wang Y; Shi D; Tan Z; Niu Y; Jiang Y; Xiong R; Peng G; He M
Front Med (Lausanne); 2021; 8():740987. PubMed ID: 34901058
[No Abstract] [Full Text] [Related]
2. 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]
3. Development and validation of a deep-learning algorithm for the detection of neovascular age-related macular degeneration from colour fundus photographs.
Keel S; Li Z; Scheetz J; Robman L; Phung J; Makeyeva G; Aung K; Liu C; Yan X; Meng W; Guymer R; Chang R; He M
Clin Exp Ophthalmol; 2019 Nov; 47(8):1009-1018. PubMed ID: 31215760
[TBL] [Abstract][Full Text] [Related]
4. Automated Diabetic Retinopathy Image Assessment Software: Diagnostic Accuracy and Cost-Effectiveness Compared with Human Graders.
Tufail A; Rudisill C; Egan C; Kapetanakis VV; Salas-Vega S; Owen CG; Lee A; Louw V; Anderson J; Liew G; Bolter L; Srinivas S; Nittala M; Sadda S; Taylor P; Rudnicka AR
Ophthalmology; 2017 Mar; 124(3):343-351. PubMed ID: 28024825
[TBL] [Abstract][Full Text] [Related]
5. Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.
Bellemo V; Lim ZW; Lim G; Nguyen QD; Xie Y; Yip MYT; Hamzah H; Ho J; Lee XQ; Hsu W; Lee ML; Musonda L; Chandran M; Chipalo-Mutati G; Muma M; Tan GSW; Sivaprasad S; Menon G; Wong TY; Ting DSW
Lancet Digit Health; 2019 May; 1(1):e35-e44. PubMed ID: 33323239
[TBL] [Abstract][Full Text] [Related]
6. An observational study to assess if automated diabetic retinopathy image assessment software can replace one or more steps of manual imaging grading and to determine their cost-effectiveness.
Tufail A; Kapetanakis VV; Salas-Vega S; Egan C; Rudisill C; Owen CG; Lee A; Louw V; Anderson J; Liew G; Bolter L; Bailey C; Sadda S; Taylor P; Rudnicka AR
Health Technol Assess; 2016 Dec; 20(92):1-72. PubMed ID: 27981917
[TBL] [Abstract][Full Text] [Related]
7. Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.
Heydon P; Egan C; Bolter L; Chambers R; Anderson J; Aldington S; Stratton IM; Scanlon PH; Webster L; Mann S; du Chemin A; Owen CG; Tufail A; Rudnicka AR
Br J Ophthalmol; 2021 May; 105(5):723-728. PubMed ID: 32606081
[TBL] [Abstract][Full Text] [Related]
8. A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.
Li N; Ma M; Lai M; Gu L; Kang M; Wang Z; Jiao S; Dang K; Deng J; Ding X; Zhen Q; Zhang A; Shen T; Zheng Z; Wang Y; Peng Y
J Diabetes; 2022 Feb; 14(2):111-120. PubMed ID: 34889059
[TBL] [Abstract][Full Text] [Related]
9. Automated Identification of Diabetic Retinopathy Using Deep Learning.
Gargeya R; Leng T
Ophthalmology; 2017 Jul; 124(7):962-969. PubMed ID: 28359545
[TBL] [Abstract][Full Text] [Related]
10. Testing a Deep Learning Algorithm for Detection of Diabetic Retinopathy in a Spanish Diabetic Population and with MESSIDOR Database.
Baget-Bernaldiz M; Pedro RA; Santos-Blanco E; Navarro-Gil R; Valls A; Moreno A; Rashwan HA; Puig D
Diagnostics (Basel); 2021 Jul; 11(8):. PubMed ID: 34441319
[TBL] [Abstract][Full Text] [Related]
11. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
Gulshan V; Peng L; Coram M; Stumpe MC; Wu D; Narayanaswamy A; Venugopalan S; Widner K; Madams T; Cuadros J; Kim R; Raman R; Nelson PC; Mega JL; Webster DR
JAMA; 2016 Dec; 316(22):2402-2410. PubMed ID: 27898976
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study.
Zhang G; Lin JW; Wang J; Ji J; Cen LP; Chen W; Xie P; Zheng Y; Xiong Y; Wu H; Li D; Ng TK; Pang CP; Zhang M
BMJ Open; 2022 Jul; 12(7):e060155. PubMed ID: 35902186
[TBL] [Abstract][Full Text] [Related]
14. Automated diabetic retinopathy screening for primary care settings using deep learning.
Bhuiyan A; Govindaiah A; Deobhakta A; Hossain M; Rosen R; Smith T
Intell Based Med; 2021; 5():. PubMed ID: 35528965
[TBL] [Abstract][Full Text] [Related]
15. Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System.
van der Heijden AA; Abramoff MD; Verbraak F; van Hecke MV; Liem A; Nijpels G
Acta Ophthalmol; 2018 Feb; 96(1):63-68. PubMed ID: 29178249
[TBL] [Abstract][Full Text] [Related]
16. Impact of targeted diabetic retinopathy training for graders in Vietnam and the implications for future diabetic retinopathy screening programmes: a diagnostic test accuracy study.
Curran K; Congdon N; Hoang TT; Lohfeld L; Nguyen VT; Nguyen HT; Nguyen QN; Dardis C; Virgili G; Piyasena P; Tran H; Salongcay RP; Tung MQ; Peto T
BMJ Open; 2022 Sep; 12(9):e059205. PubMed ID: 36691192
[TBL] [Abstract][Full Text] [Related]
17. Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study.
Xie Y; Nguyen QD; Hamzah H; Lim G; Bellemo V; Gunasekeran DV; Yip MYT; Qi Lee X; Hsu W; Li Lee M; Tan CS; Tym Wong H; Lamoureux EL; Tan GSW; Wong TY; Finkelstein EA; Ting DSW
Lancet Digit Health; 2020 May; 2(5):e240-e249. PubMed ID: 33328056
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.
Phene S; Dunn RC; Hammel N; Liu Y; Krause J; Kitade N; Schaekermann M; Sayres R; Wu DJ; Bora A; Semturs C; Misra A; Huang AE; Spitze A; Medeiros FA; Maa AY; Gandhi M; Corrado GS; Peng L; Webster DR
Ophthalmology; 2019 Dec; 126(12):1627-1639. PubMed ID: 31561879
[TBL] [Abstract][Full Text] [Related]
19. Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.
Liu H; Li L; Wormstone IM; Qiao C; Zhang C; Liu P; Li S; Wang H; Mou D; Pang R; Yang D; Zangwill LM; Moghimi S; Hou H; Bowd C; Jiang L; Chen Y; Hu M; Xu Y; Kang H; Ji X; Chang R; Tham C; Cheung C; Ting DSW; Wong TY; Wang Z; Weinreb RN; Xu M; Wang N
JAMA Ophthalmol; 2019 Dec; 137(12):1353-1360. PubMed ID: 31513266
[TBL] [Abstract][Full Text] [Related]
20. Deep learning detection of diabetic retinopathy in Scotland's diabetic eye screening programme.
Fleming AD; Mellor J; McGurnaghan SJ; Blackbourn LAK; Goatman KA; Styles C; Storkey AJ; McKeigue PM; Colhoun HM
Br J Ophthalmol; 2023 Sep; ():. PubMed ID: 37704266
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
