227 related articles for article (PubMed ID: 32341536)
1. Comparison of automated and expert human grading of diabetic retinopathy using smartphone-based retinal photography.
Kim TN; Aaberg MT; Li P; Davila JR; Bhaskaranand M; Bhat S; Ramachandra C; Solanki K; Myers F; Reber C; Jalalizadeh R; Margolis TP; Fletcher D; Paulus YM
Eye (Lond); 2021 Jan; 35(1):334-342. PubMed ID: 32341536
[TBL] [Abstract][Full Text] [Related]
2. EyeArt artificial intelligence analysis of diabetic retinopathy in retinal screening events.
Vought R; Vought V; Shah M; Szirth B; Bhagat N
Int Ophthalmol; 2023 Dec; 43(12):4851-4859. PubMed ID: 37847478
[TBL] [Abstract][Full Text] [Related]
3. Validation of diagnostic accuracy of retinal image grading by trained non-ophthalmologist grader for detecting diabetic retinopathy and diabetic macular edema.
Joseph S; Rajan RP; Sundar B; Venkatachalam S; Kempen JH; Kim R
Eye (Lond); 2023 Jun; 37(8):1577-1582. PubMed ID: 35906419
[TBL] [Abstract][Full Text] [Related]
4. Accuracy and reliability of retinal photo grading for diabetic retinopathy: Remote graders from a developing country and standard retinal photo grader in Australia.
Islam FMA
PLoS One; 2017; 12(6):e0179310. PubMed ID: 28632764
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.
Piyasena MMPN; Yip JLY; MacLeod D; Kim M; Gudlavalleti VSM
BMC Ophthalmol; 2019 Apr; 19(1):89. PubMed ID: 30961576
[TBL] [Abstract][Full Text] [Related]
7. Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence.
Rajalakshmi R; Subashini R; Anjana RM; Mohan V
Eye (Lond); 2018 Jun; 32(6):1138-1144. PubMed ID: 29520050
[TBL] [Abstract][Full Text] [Related]
8. Validation of Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening.
Bilong Y; Katte JC; Koki G; Kagmeni G; Obama OPN; Fofe HRN; Mvilongo C; Nkengfack O; Bimbai AM; Sobngwi E; Mbacham W; Mbanya JC; Bella LA; Sharma A
Ophthalmic Surg Lasers Imaging Retina; 2019 May; 50(5):S18-S22. PubMed ID: 31100178
[TBL] [Abstract][Full Text] [Related]
9. Multimodal imaging interpreted by graders to detect re-activation of diabetic eye disease in previously treated patients: the EMERALD diagnostic accuracy study.
Lois N; Cook J; Wang A; Aldington S; Mistry H; Maredza M; McAuley D; Aslam T; Bailey C; Chong V; Ghanchi F; Scanlon P; Sivaprasad S; Steel D; Styles C; Azuara-Blanco A; Prior L; Waugh N
Health Technol Assess; 2021 May; 25(32):1-104. PubMed ID: 34060440
[TBL] [Abstract][Full Text] [Related]
10. Validation of Smartphone Based Retinal Photography for Diabetic Retinopathy Screening.
Rajalakshmi R; Arulmalar S; Usha M; Prathiba V; Kareemuddin KS; Anjana RM; Mohan V
PLoS One; 2015; 10(9):e0138285. PubMed ID: 26401839
[TBL] [Abstract][Full Text] [Related]
11. Web-based grading of compressed stereoscopic digital photography versus standard slide film photography for the diagnosis of diabetic retinopathy.
Rudnisky CJ; Tennant MT; Weis E; Ting A; Hinz BJ; Greve MD
Ophthalmology; 2007 Sep; 114(9):1748-54. PubMed ID: 17368543
[TBL] [Abstract][Full Text] [Related]
12. Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy.
Prathiba V; Rajalakshmi R; Arulmalar S; Usha M; Subhashini R; Gilbert CE; Anjana RM; Mohan V
Indian J Ophthalmol; 2020 Feb; 68(Suppl 1):S42-S46. PubMed ID: 31937728
[TBL] [Abstract][Full Text] [Related]
13. Clinical validation of a smartphone-based retinal camera for diabetic retinopathy screening.
de Oliveira JAE; Nakayama LF; Zago Ribeiro L; de Oliveira TVF; Choi SNJH; Neto EM; Cardoso VS; Dib SA; Melo GB; Regatieri CVS; Malerbi FK
Acta Diabetol; 2023 Aug; 60(8):1075-1081. PubMed ID: 37149834
[TBL] [Abstract][Full Text] [Related]
14. Effectiveness and safety of screening for diabetic retinopathy with two nonmydriatic digital images compared with the seven standard stereoscopic photographic fields.
Boucher MC; Gresset JA; Angioi K; Olivier S
Can J Ophthalmol; 2003 Dec; 38(7):557-68. PubMed ID: 14740797
[TBL] [Abstract][Full Text] [Related]
15. Validity of smartphone-based retinal photography (PEEK-retina) compared to the standard ophthalmic fundus camera in diagnosing diabetic retinopathy in Uganda: A cross-sectional study.
Yusuf AM; Lusobya RC; Mukisa J; Batte C; Nakanjako D; Juliet-Sengeri O
PLoS One; 2022; 17(9):e0273633. PubMed ID: 36067194
[TBL] [Abstract][Full Text] [Related]
16. Interobserver agreement in the interpretation of single-field digital fundus images for diabetic retinopathy screening.
Ruamviboonsuk P; Teerasuwanajak K; Tiensuwan M; Yuttitham K;
Ophthalmology; 2006 May; 113(5):826-32. PubMed ID: 16650679
[TBL] [Abstract][Full Text] [Related]
17. Sensitivity and Specificity of Smartphone-Based Retinal Imaging for Diabetic Retinopathy: A Comparative Study.
Sengupta S; Sindal MD; Baskaran P; Pan U; Venkatesh R
Ophthalmol Retina; 2019 Feb; 3(2):146-153. PubMed ID: 31014763
[TBL] [Abstract][Full Text] [Related]
18. The Value of Automated Diabetic Retinopathy Screening with the EyeArt System: A Study of More Than 100,000 Consecutive Encounters from People with Diabetes.
Bhaskaranand M; Ramachandra C; Bhat S; Cuadros J; Nittala MG; Sadda SR; Solanki K
Diabetes Technol Ther; 2019 Nov; 21(11):635-643. PubMed ID: 31335200
[No Abstract] [Full Text] [Related]
19. Automated diabetic retinopathy detection with two different retinal imaging devices using artificial intelligence: a comparison study.
Sarao V; Veritti D; Lanzetta P
Graefes Arch Clin Exp Ophthalmol; 2020 Dec; 258(12):2647-2654. PubMed ID: 32936359
[TBL] [Abstract][Full Text] [Related]
20. Automated analysis of retinal images for detection of referable diabetic retinopathy.
Abràmoff MD; Folk JC; Han DP; Walker JD; Williams DF; Russell SR; Massin P; Cochener B; Gain P; Tang L; Lamard M; Moga DC; Quellec G; Niemeijer M
JAMA Ophthalmol; 2013 Mar; 131(3):351-7. PubMed ID: 23494039
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]