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.
210 related articles for article (PubMed ID: 34723902)
1. DEVELOPMENT AND VALIDATION OF AN EXPLAINABLE ARTIFICIAL INTELLIGENCE FRAMEWORK FOR MACULAR DISEASE DIAGNOSIS BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES. Lv B; Li S; Liu Y; Wang W; Li H; Zhang X; Sha Y; Yang X; Yang Y; Wang Y; Zhang C; Wang Y; Lv C; Xie G; Wang K Retina; 2022 Mar; 42(3):456-464. PubMed ID: 34723902 [TBL] [Abstract][Full Text] [Related]
2. Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning. Schlegl T; Waldstein SM; Bogunovic H; Endstraßer F; Sadeghipour A; Philip AM; Podkowinski D; Gerendas BS; Langs G; Schmidt-Erfurth U Ophthalmology; 2018 Apr; 125(4):549-558. PubMed ID: 29224926 [TBL] [Abstract][Full Text] [Related]
3. Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography. Perdomo O; Rios H; Rodríguez FJ; Otálora S; Meriaudeau F; Müller H; González FA Comput Methods Programs Biomed; 2019 Sep; 178():181-189. PubMed ID: 31416547 [TBL] [Abstract][Full Text] [Related]
4. DISEASE CLASSIFICATION OF MACULAR OPTICAL COHERENCE TOMOGRAPHY SCANS USING DEEP LEARNING SOFTWARE: Validation on Independent, Multicenter Data. Bhatia KK; Graham MS; Terry L; Wood A; Tranos P; Trikha S; Jaccard N Retina; 2020 Aug; 40(8):1549-1557. PubMed ID: 31584557 [TBL] [Abstract][Full Text] [Related]
5. A novel approach for automatic classification of macular degeneration OCT images. Pang S; Zou B; Xiao X; Peng Q; Yan J; Zhang W; Yue K Sci Rep; 2024 Aug; 14(1):19285. PubMed ID: 39164445 [TBL] [Abstract][Full Text] [Related]
6. RD-OCT net: hybrid learning system for automated diagnosis of macular diseases from OCT retinal images. Prabha AJ; Venkatesan C; Fathimal MS; Nithiyanantham KK; Kirubha SPA Biomed Phys Eng Express; 2024 Feb; 10(2):. PubMed ID: 38335542 [TBL] [Abstract][Full Text] [Related]
7. Spectral domain optical coherence tomography classification of diabetic macular edema: a new proposal to clinical practice. Arf S; Sayman Muslubas I; Hocaoglu M; Ersoz MG; Ozdemir H; Karacorlu M Graefes Arch Clin Exp Ophthalmol; 2020 Jun; 258(6):1165-1172. PubMed ID: 32152718 [TBL] [Abstract][Full Text] [Related]
8. Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning. Wilson M; Chopra R; Wilson MZ; Cooper C; MacWilliams P; Liu Y; Wulczyn E; Florea D; Hughes CO; Karthikesalingam A; Khalid H; Vermeirsch S; Nicholson L; Keane PA; Balaskas K; Kelly CJ JAMA Ophthalmol; 2021 Sep; 139(9):964-973. PubMed ID: 34236406 [TBL] [Abstract][Full Text] [Related]
9. Explainable ensemble learning method for OCT detection with transfer learning. Yang J; Wang G; Xiao X; Bao M; Tian G PLoS One; 2024; 19(3):e0296175. PubMed ID: 38517913 [TBL] [Abstract][Full Text] [Related]
10. Fully automated detection of retinal disorders by image-based deep learning. Li F; Chen H; Liu Z; Zhang X; Wu Z Graefes Arch Clin Exp Ophthalmol; 2019 Mar; 257(3):495-505. PubMed ID: 30610422 [TBL] [Abstract][Full Text] [Related]
11. Spectral Domain Optical Coherence Tomography Features and Classification Systems for Diabetic Macular Edema: A Review. Ruia S; Saxena S; Gemmy Cheung CM; Gilhotra JS; Lai TY Asia Pac J Ophthalmol (Phila); 2016; 5(5):360-7. PubMed ID: 27632028 [TBL] [Abstract][Full Text] [Related]
12. 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]
13. Automated classification of choroidal neovascularization, diabetic macular edema, and drusen from retinal OCT images using vision transformers: a comparative study. Akça S; Garip Z; Ekinci E; Atban F Lasers Med Sci; 2024 May; 39(1):140. PubMed ID: 38797751 [TBL] [Abstract][Full Text] [Related]
14. Application of artificial intelligence-based dual-modality analysis combining fundus photography and optical coherence tomography in diabetic retinopathy screening in a community hospital. Liu R; Li Q; Xu F; Wang S; He J; Cao Y; Shi F; Chen X; Chen J Biomed Eng Online; 2022 Jul; 21(1):47. PubMed ID: 35859144 [TBL] [Abstract][Full Text] [Related]
16. Effect of segmentation error correction on optical coherence tomography angiography measurements in healthy subjects and diabetic macular oedema. Ghasemi Falavarjani K; Habibi A; Anvari P; Ghasemizadeh S; Ashraf Khorasani M; Shenazandi H; Sarraf D Br J Ophthalmol; 2020 Feb; 104(2):162-166. PubMed ID: 31036586 [TBL] [Abstract][Full Text] [Related]
17. Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization. Khan A; Pin K; Aziz A; Han JW; Nam Y Sensors (Basel); 2023 Jul; 23(15):. PubMed ID: 37571490 [TBL] [Abstract][Full Text] [Related]
18. Vision-Language Models for Feature Detection of Macular Diseases on Optical Coherence Tomography. Antaki F; Chopra R; Keane PA JAMA Ophthalmol; 2024 Jun; 142(6):573-576. PubMed ID: 38696177 [TBL] [Abstract][Full Text] [Related]
19. Etiology of Macular Edema Defined by Deep Learning in Optical Coherence Tomography Scans. Padilla-Pantoja FD; Sanchez YD; Quijano-Nieto BA; Perdomo OJ; Gonzalez FA Transl Vis Sci Technol; 2022 Sep; 11(9):29. PubMed ID: 36169966 [TBL] [Abstract][Full Text] [Related]
20. Optical coherence tomography-based diabetic macula edema screening with artificial intelligence. Hwang DK; Chou YB; Lin TC; Yang HY; Kao ZK; Kao CL; Yang YP; Chen SJ; Hsu CC; Jheng YC J Chin Med Assoc; 2020 Nov; 83(11):1034-1038. PubMed ID: 32452907 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]