215 related articles for article (PubMed ID: 35473414)
1. Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.
Li HY; Wang DX; Dong L; Wei WB
Eur J Ophthalmol; 2023 Jan; 33(1):278-290. PubMed ID: 35473414
[TBL] [Abstract][Full Text] [Related]
2. Performance of Artificial Intelligence in Detecting Diabetic Macular Edema From Fundus Photography and Optical Coherence Tomography Images: A Systematic Review and Meta-analysis.
Lam C; Wong YL; Tang Z; Hu X; Nguyen TX; Yang D; Zhang S; Ding J; Szeto SKH; Ran AR; Cheung CY
Diabetes Care; 2024 Feb; 47(2):304-319. PubMed ID: 38241500
[TBL] [Abstract][Full Text] [Related]
3. DETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.
Wu Q; Zhang B; Hu Y; Liu B; Cao D; Yang D; Peng Q; Zhong P; Zeng X; Xiao Y; Li C; Fang Y; Feng S; Huang M; Cai H; Yang X; Yu H
Retina; 2021 May; 41(5):1110-1117. PubMed ID: 33031250
[TBL] [Abstract][Full Text] [Related]
4. Artificial intelligence in screening, diagnosis, and classification of diabetic macular edema: A systematic review.
Shahriari MH; Sabbaghi H; Asadi F; Hosseini A; Khorrami Z
Surv Ophthalmol; 2023; 68(1):42-53. PubMed ID: 35970233
[TBL] [Abstract][Full Text] [Related]
5. Optical coherence tomography (OCT) for detection of macular oedema in patients with diabetic retinopathy.
Virgili G; Menchini F; Murro V; Peluso E; Rosa F; Casazza G
Cochrane Database Syst Rev; 2011 Jul; (7):CD008081. PubMed ID: 21735421
[TBL] [Abstract][Full Text] [Related]
6. Performance of deep neural network-based artificial intelligence method in diabetic retinopathy screening: a systematic review and meta-analysis of diagnostic test accuracy.
Wang S; Zhang Y; Lei S; Zhu H; Li J; Wang Q; Yang J; Chen S; Pan H
Eur J Endocrinol; 2020 Jun; 183(1):41-49. PubMed ID: 32504495
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Deep Learning to Detect OCT-derived Diabetic Macular Edema from Color Retinal Photographs: A Multicenter Validation Study.
Liu X; Ali TK; Singh P; Shah A; McKinney SM; Ruamviboonsuk P; Turner AW; Keane PA; Chotcomwongse P; Nganthavee V; Chia M; Huemer J; Cuadros J; Raman R; Corrado GS; Peng L; Webster DR; Hammel N; Varadarajan AV; Liu Y; Chopra R; Bavishi P
Ophthalmol Retina; 2022 May; 6(5):398-410. PubMed ID: 34999015
[TBL] [Abstract][Full Text] [Related]
9. Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?
Bar-David D; Bar-David L; Shapira Y; Leibu R; Dori D; Gebara A; Schneor R; Fischer A; Soudry S
IEEE J Transl Eng Health Med; 2023; 11():487-494. PubMed ID: 37817823
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Deep Learning Predicts OCT Measures of Diabetic Macular Thickening From Color Fundus Photographs.
Arcadu F; Benmansour F; Maunz A; Michon J; Haskova Z; McClintock D; Adamis AP; Willis JR; Prunotto M
Invest Ophthalmol Vis Sci; 2019 Mar; 60(4):852-857. PubMed ID: 30821810
[TBL] [Abstract][Full Text] [Related]
12. Optical coherence tomography versus stereoscopic fundus photography or biomicroscopy for diagnosing diabetic macular edema: a systematic review.
Virgili G; Menchini F; Dimastrogiovanni AF; Rapizzi E; Menchini U; Bandello F; Chiodini RG
Invest Ophthalmol Vis Sci; 2007 Nov; 48(11):4963-73. PubMed ID: 17962446
[TBL] [Abstract][Full Text] [Related]
13. A new intelligent system based deep learning to detect DME and AMD in OCT images.
Gueddena Y; Aboudi N; Zgolli H; Mabrouk S; Sidibe D; Tabia H; Khlifa N
Int Ophthalmol; 2024 Apr; 44(1):191. PubMed ID: 38653842
[TBL] [Abstract][Full Text] [Related]
14. Prevalence of diabetic macular edema based on optical coherence tomography in people with diabetes: A systematic review and meta-analysis.
Im JHB; Jin YP; Chow R; Yan P
Surv Ophthalmol; 2022; 67(4):1244-1251. PubMed ID: 35093404
[TBL] [Abstract][Full Text] [Related]
15. A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.
Tang F; Wang X; Ran AR; Chan CKM; Ho M; Yip W; Young AL; Lok J; Szeto S; Chan J; Yip F; Wong R; Tang Z; Yang D; Ng DS; Chen LJ; Brelén M; Chu V; Li K; Lai THT; Tan GS; Ting DSW; Huang H; Chen H; Ma JH; Tang S; Leng T; Kakavand S; Mannil SS; Chang RT; Liew G; Gopinath B; Lai TYY; Pang CP; Scanlon PH; Wong TY; Tham CC; Chen H; Heng PA; Cheung CY
Diabetes Care; 2021 Sep; 44(9):2078-2088. PubMed ID: 34315698
[TBL] [Abstract][Full Text] [Related]
16. Detection of Diabetic Macular Edema in Optical Coherence Tomography Image Using an Improved Level Set Algorithm.
Wang Z; Zhang W; Sun Y; Yao M; Yan B
Biomed Res Int; 2020; 2020():6974215. PubMed ID: 32420362
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. 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]
19. 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]
20. Smartphone-based diabetic macula edema screening with an offline artificial intelligence.
Hwang DK; Yu WK; Lin TC; Chou SJ; Yarmishyn A; Kao ZK; Kao CL; Yang YP; Chen SJ; Hsu CC; Jheng YC
J Chin Med Assoc; 2020 Dec; 83(12):1102-1106. PubMed ID: 33210900
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
