1855 related articles for article (PubMed ID: 31957737)
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. Automatic Detection of Diabetic Retinopathy in Retinal Fundus Photographs Based on Deep Learning Algorithm.
Li F; Liu Z; Chen H; Jiang M; Zhang X; Wu Z
Transl Vis Sci Technol; 2019 Nov; 8(6):4. PubMed ID: 31737428
[TBL] [Abstract][Full Text] [Related]
23. 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]
24. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications.
Prahs P; Radeck V; Mayer C; Cvetkov Y; Cvetkova N; Helbig H; Märker D
Graefes Arch Clin Exp Ophthalmol; 2018 Jan; 256(1):91-98. PubMed ID: 29127485
[TBL] [Abstract][Full Text] [Related]
25. Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy.
Krause J; Gulshan V; Rahimy E; Karth P; Widner K; Corrado GS; Peng L; Webster DR
Ophthalmology; 2018 Aug; 125(8):1264-1272. PubMed ID: 29548646
[TBL] [Abstract][Full Text] [Related]
26. Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy.
Le D; Alam M; Yao CK; Lim JI; Hsieh YT; Chan RVP; Toslak D; Yao X
Transl Vis Sci Technol; 2020 Jul; 9(2):35. PubMed ID: 32855839
[TBL] [Abstract][Full Text] [Related]
27. 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]
28. 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]
29. Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program.
Salongcay RP; Aquino LAC; Alog GP; Locaylocay KB; Saunar AV; Peto T; Silva PS
Ophthalmol Sci; 2024; 4(3):100457. PubMed ID: 38317871
[TBL] [Abstract][Full Text] [Related]
30. Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration.
González-Gonzalo C; Sánchez-Gutiérrez V; Hernández-Martínez P; Contreras I; Lechanteur YT; Domanian A; van Ginneken B; Sánchez CI
Acta Ophthalmol; 2020 Jun; 98(4):368-377. PubMed ID: 31773912
[TBL] [Abstract][Full Text] [Related]
31. [Using artificial intelligence as an initial triage strategy in diabetic retinopathy screening program in China].
Li ZX; Zhang J; Fong N; He MG
Zhonghua Yi Xue Za Zhi; 2020 Dec; 100(48):3835-3840. PubMed ID: 33371627
[No Abstract] [Full Text] [Related]
32. Application of deep learning image assessment software VeriSee™ for diabetic retinopathy screening.
Hsieh YT; Chuang LM; Jiang YD; Chang TJ; Yang CM; Yang CH; Chan LW; Kao TY; Chen TC; Lin HC; Tsai CH; Chen M
J Formos Med Assoc; 2021 Jan; 120(1 Pt 1):165-171. PubMed ID: 32307321
[TBL] [Abstract][Full Text] [Related]
33. Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma.
Surya J; Garima ; Pandy N; Hyungtaek Rim T; Lee G; Priya MNS; Subramanian B; Raman R
Indian J Ophthalmol; 2023 Aug; 71(8):3039-3045. PubMed ID: 37530278
[TBL] [Abstract][Full Text] [Related]
34. Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases.
Burlina P; Paul W; Mathew P; Joshi N; Pacheco KD; Bressler NM
JAMA Ophthalmol; 2020 Oct; 138(10):1070-1077. PubMed ID: 32880609
[TBL] [Abstract][Full Text] [Related]
35. Clinician-Driven AI: Code-Free Self-Training on Public Data for Diabetic Retinopathy Referral.
Korot E; Gonçalves MB; Huemer J; Beqiri S; Khalid H; Kelly M; Chia M; Mathijs E; Struyven R; Moussa M; Keane PA
JAMA Ophthalmol; 2023 Nov; 141(11):1029-1036. PubMed ID: 37856110
[TBL] [Abstract][Full Text] [Related]
36. Deep Learning-Based Algorithms in Screening of Diabetic Retinopathy: A Systematic Review of Diagnostic Performance.
Nielsen KB; Lautrup ML; Andersen JKH; Savarimuthu TR; Grauslund J
Ophthalmol Retina; 2019 Apr; 3(4):294-304. PubMed ID: 31014679
[TBL] [Abstract][Full Text] [Related]
37. Towards a Device Agnostic AI for Diabetic Retinopathy Screening: An External Validation Study.
Rao DP; Sindal MD; Sengupta S; Baskaran P; Venkatesh R; Sivaraman A; Savoy FM
Clin Ophthalmol; 2022; 16():2659-2667. PubMed ID: 36003071
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. Detection of Diabetic Retinopathy from Ultra-Widefield Scanning Laser Ophthalmoscope Images: A Multicenter Deep Learning Analysis.
Tang F; Luenam P; Ran AR; Quadeer AA; Raman R; Sen P; Khan R; Giridhar A; Haridas S; Iglicki M; Zur D; Loewenstein A; Negri HP; Szeto S; Lam BKY; Tham CC; Sivaprasad S; Mckay M; Cheung CY
Ophthalmol Retina; 2021 Nov; 5(11):1097-1106. PubMed ID: 33540169
[TBL] [Abstract][Full Text] [Related]
40. Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.
Son J; Shin JY; Kim HD; Jung KH; Park KH; Park SJ
Ophthalmology; 2020 Jan; 127(1):85-94. PubMed ID: 31281057
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]