302 related articles for article (PubMed ID: 33388480)
1. Development of a deep learning-based image eligibility verification system for detecting and filtering out ineligible fundus images: A multicentre study.
Li Z; Jiang J; Zhou H; Zheng Q; Liu X; Chen K; Weng H; Chen W
Int J Med Inform; 2021 Mar; 147():104363. PubMed ID: 33388480
[TBL] [Abstract][Full Text] [Related]
2. Development of a deep learning-based image quality control system to detect and filter out ineligible slit-lamp images: A multicenter study.
Li Z; Jiang J; Chen K; Zheng Q; Liu X; Weng H; Wu S; Chen W
Comput Methods Programs Biomed; 2021 May; 203():106048. PubMed ID: 33765481
[TBL] [Abstract][Full Text] [Related]
3. A Deep Learning-Based Algorithm Identifies Glaucomatous Discs Using Monoscopic Fundus Photographs.
Liu S; Graham SL; Schulz A; Kalloniatis M; Zangerl B; Cai W; Gao Y; Chua B; Arvind H; Grigg J; Chu D; Klistorner A; You Y
Ophthalmol Glaucoma; 2018; 1(1):15-22. PubMed ID: 32672627
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.
Lin D; Xiong J; Liu C; Zhao L; Li Z; Yu S; Wu X; Ge Z; Hu X; Wang B; Fu M; Zhao X; Wang X; Zhu Y; Chen C; Li T; Li Y; Wei W; Zhao M; Li J; Xu F; Ding L; Tan G; Xiang Y; Hu Y; Zhang P; Han Y; Li JO; Wei L; Zhu P; Liu Y; Chen W; Ting DSW; Wong TY; Chen Y; Lin H
Lancet Digit Health; 2021 Aug; 3(8):e486-e495. PubMed ID: 34325853
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and "Plus" Lesion Detection in Fundus Images.
Lu L; Ren P; Tang X; Yang M; Yuan M; Yu W; Huang J; Zhou E; Lu L; He Q; Zhu M; Ke G; Han W
Front Cell Dev Biol; 2021; 9():719262. PubMed ID: 34722502
[No Abstract] [Full Text] [Related]
8. Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.
Xiao W; Huang X; Wang JH; Lin DR; Zhu Y; Chen C; Yang YH; Xiao J; Zhao LQ; Li JO; Cheung CY; Mise Y; Guo ZY; Du YF; Chen BB; Hu JX; Zhang K; Lin XS; Wen W; Liu YZ; Chen WR; Zhong YS; Lin HT
Lancet Digit Health; 2021 Feb; 3(2):e88-e97. PubMed ID: 33509389
[TBL] [Abstract][Full Text] [Related]
9. Application of an Anomaly Detection Model to Screen for Ocular Diseases Using Color Retinal Fundus Images: Design and Evaluation Study.
Han Y; Li W; Liu M; Wu Z; Zhang F; Liu X; Tao L; Li X; Guo X
J Med Internet Res; 2021 Jul; 23(7):e27822. PubMed ID: 34255681
[TBL] [Abstract][Full Text] [Related]
10. Artificial Intelligence-Assisted Early Detection of Retinitis Pigmentosa - the Most Common Inherited Retinal Degeneration.
Chen TC; Lim WS; Wang VY; Ko ML; Chiu SI; Huang YS; Lai F; Yang CM; Hu FR; Jang JR; Yang CH
J Digit Imaging; 2021 Aug; 34(4):948-958. PubMed ID: 34244880
[TBL] [Abstract][Full Text] [Related]
11. Autonomous screening for laser photocoagulation in fundus images using deep learning.
Bressler I; Aviv R; Margalit D; Rom Y; Ianchulev T; Dvey-Aharon Z
Br J Ophthalmol; 2024 May; 108(5):742-746. PubMed ID: 37217293
[TBL] [Abstract][Full Text] [Related]
12. Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study.
Tan TE; Anees A; Chen C; Li S; Xu X; Li Z; Xiao Z; Yang Y; Lei X; Ang M; Chia A; Lee SY; Wong EYM; Yeo IYS; Wong YL; Hoang QV; Wang YX; Bikbov MM; Nangia V; Jonas JB; Chen YP; Wu WC; Ohno-Matsui K; Rim TH; Tham YC; Goh RSM; Lin H; Liu H; Wang N; Yu W; Tan DTH; Schmetterer L; Cheng CY; Chen Y; Wong CW; Cheung GCM; Saw SM; Wong TY; Liu Y; Ting DSW
Lancet Digit Health; 2021 May; 3(5):e317-e329. PubMed ID: 33890579
[TBL] [Abstract][Full Text] [Related]
13. Development of an artificial intelligence system to classify pathology and clinical features on retinal fundus images.
Stevenson CH; Hong SC; Ogbuehi KC
Clin Exp Ophthalmol; 2019 May; 47(4):484-489. PubMed ID: 30370587
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.
Li F; Yan L; Wang Y; Shi J; Chen H; Zhang X; Jiang M; Wu Z; Zhou K
Graefes Arch Clin Exp Ophthalmol; 2020 Apr; 258(4):851-867. PubMed ID: 31989285
[TBL] [Abstract][Full Text] [Related]
16. Deep learning from "passive feeding" to "selective eating" of real-world data.
Li Z; Guo C; Nie D; Lin D; Zhu Y; Chen C; Zhao L; Wu X; Dongye M; Xu F; Jin C; Zhang P; Han Y; Yan P; Lin H
NPJ Digit Med; 2020; 3():143. PubMed ID: 33145439
[TBL] [Abstract][Full Text] [Related]
17. A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study.
Zou XL; Ren Y; Feng DY; He XQ; Guo YF; Yang HL; Li X; Fang J; Li Q; Ye JJ; Han LQ; Zhang TT
PLoS One; 2020; 15(7):e0236378. PubMed ID: 32706807
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.
Coyner AS; Swan R; Brown JM; Kalpathy-Cramer J; Kim SJ; Campbell JP; Jonas KE; Ostmo S; Chan RVP; Chiang MF
AMIA Annu Symp Proc; 2018; 2018():1224-1232. PubMed ID: 30815164
[TBL] [Abstract][Full Text] [Related]
19. Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.
Phene S; Dunn RC; Hammel N; Liu Y; Krause J; Kitade N; Schaekermann M; Sayres R; Wu DJ; Bora A; Semturs C; Misra A; Huang AE; Spitze A; Medeiros FA; Maa AY; Gandhi M; Corrado GS; Peng L; Webster DR
Ophthalmology; 2019 Dec; 126(12):1627-1639. PubMed ID: 31561879
[TBL] [Abstract][Full Text] [Related]
20. A self-adaptive deep learning method for automated eye laterality detection based on color fundus photography.
Liu C; Han X; Li Z; Ha J; Peng G; Meng W; He M
PLoS One; 2019; 14(9):e0222025. PubMed ID: 31536537
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]