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.
347 related articles for article (PubMed ID: 31358385)
1. A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs. Keenan TD; Dharssi S; Peng Y; Chen Q; Agrón E; Wong WT; Lu Z; Chew EY Ophthalmology; 2019 Nov; 126(11):1533-1540. PubMed ID: 31358385 [TBL] [Abstract][Full Text] [Related]
2. DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs. Peng Y; Dharssi S; Chen Q; Keenan TD; Agrón E; Wong WT; Chew EY; Lu Z Ophthalmology; 2019 Apr; 126(4):565-575. PubMed ID: 30471319 [TBL] [Abstract][Full Text] [Related]
3. Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2. Keenan TDL; Chen Q; Peng Y; Domalpally A; Agrón E; Hwang CK; Thavikulwat AT; Lee DH; Li D; Wong WT; Lu Z; Chew EY Ophthalmology; 2020 Dec; 127(12):1674-1687. PubMed ID: 32447042 [TBL] [Abstract][Full Text] [Related]
4. Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs. Li Z; He Y; Keel S; Meng W; Chang RT; He M Ophthalmology; 2018 Aug; 125(8):1199-1206. PubMed ID: 29506863 [TBL] [Abstract][Full Text] [Related]
5. Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier. Treder M; Lauermann JL; Eter N Graefes Arch Clin Exp Ophthalmol; 2018 Nov; 256(11):2053-2060. PubMed ID: 30091055 [TBL] [Abstract][Full Text] [Related]
6. A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography. Grassmann F; Mengelkamp J; Brandl C; Harsch S; Zimmermann ME; Linkohr B; Peters A; Heid IM; Palm C; Weber BHF Ophthalmology; 2018 Sep; 125(9):1410-1420. PubMed ID: 29653860 [TBL] [Abstract][Full Text] [Related]
7. Evaluation of Geographic Atrophy from Color Photographs and Fundus Autofluorescence Images: Age-Related Eye Disease Study 2 Report Number 11. Domalpally A; Danis R; Agrón E; Blodi B; Clemons T; Chew E; Ophthalmology; 2016 Nov; 123(11):2401-2407. PubMed ID: 27448832 [TBL] [Abstract][Full Text] [Related]
8. Automated image alignment and segmentation to follow progression of geographic atrophy in age-related macular degeneration. Ramsey DJ; Sunness JS; Malviya P; Applegate C; Hager GD; Handa JT Retina; 2014 Jul; 34(7):1296-307. PubMed ID: 24398699 [TBL] [Abstract][Full Text] [Related]
9. Deep Learning Detection of Sea Fan Neovascularization From Ultra-Widefield Color Fundus Photographs of Patients With Sickle Cell Hemoglobinopathy. Cai S; Parker F; Urias MG; Goldberg MF; Hager GD; Scott AW JAMA Ophthalmol; 2021 Feb; 139(2):206-213. PubMed ID: 33377944 [TBL] [Abstract][Full Text] [Related]
10. Automated segmentation of geographic atrophy of the retinal epithelium via random forests in AREDS color fundus images. Feeny AK; Tadarati M; Freund DE; Bressler NM; Burlina P Comput Biol Med; 2015 Oct; 65():124-36. PubMed ID: 26318113 [TBL] [Abstract][Full Text] [Related]
11. 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]
12. A Deep Learning Model for Segmentation of Geographic Atrophy to Study Its Long-Term Natural History. Liefers B; Colijn JM; González-Gonzalo C; Verzijden T; Wang JJ; Joachim N; Mitchell P; Hoyng CB; van Ginneken B; Klaver CCW; Sánchez CI Ophthalmology; 2020 Aug; 127(8):1086-1096. PubMed ID: 32197912 [TBL] [Abstract][Full Text] [Related]
13. Improving Interpretability in Machine Diagnosis: Detection of Geographic Atrophy in OCT Scans. Shi X; Keenan TDL; Chen Q; De Silva T; Thavikulwat AT; Broadhead G; Bhandari S; Cukras C; Chew EY; Lu Z Ophthalmol Sci; 2021 Sep; 1(3):100038. PubMed ID: 36247813 [TBL] [Abstract][Full Text] [Related]
14. Explainable artificial intelligence model for the detection of geographic atrophy using colour retinal photographs. Sarao V; Veritti D; De Nardin A; Misciagna M; Foresti G; Lanzetta P BMJ Open Ophthalmol; 2023 Dec; 8(1):. PubMed ID: 38057106 [TBL] [Abstract][Full Text] [Related]
15. 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]
16. Comparison of color fundus photographs and fundus autofluorescence images in measuring geographic atrophy area. Khanifar AA; Lederer DE; Ghodasra JH; Stinnett SS; Lee JJ; Cousins SW; Bearelly S Retina; 2012 Oct; 32(9):1884-91. PubMed ID: 22547167 [TBL] [Abstract][Full Text] [Related]
17. Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration. Burlina PM; Joshi N; Pacheco KD; Liu TYA; Bressler NM JAMA Ophthalmol; 2019 Mar; 137(3):258-264. PubMed ID: 30629091 [TBL] [Abstract][Full Text] [Related]
18. Self-Supervised Feature Learning and Phenotyping for Assessing Age-Related Macular Degeneration Using Retinal Fundus Images. Yellapragada B; Hornauer S; Snyder K; Yu S; Yiu G Ophthalmol Retina; 2022 Feb; 6(2):116-129. PubMed ID: 34217854 [TBL] [Abstract][Full Text] [Related]
19. Deep learning-based classification of retinal atrophy using fundus autofluorescence imaging. Miere A; Capuano V; Kessler A; Zambrowski O; Jung C; Colantuono D; Pallone C; Semoun O; Petit E; Souied E Comput Biol Med; 2021 Mar; 130():104198. PubMed ID: 33383315 [TBL] [Abstract][Full Text] [Related]
20. Detecting glaucoma from multi-modal data using probabilistic deep learning. Huang X; Sun J; Gupta K; Montesano G; Crabb DP; Garway-Heath DF; Brusini P; Lanzetta P; Oddone F; Turpin A; McKendrick AM; Johnson CA; Yousefi S Front Med (Lausanne); 2022; 9():923096. PubMed ID: 36250081 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]