120 related articles for article (PubMed ID: 38918566)
21. Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity.
Redd TK; Campbell JP; Brown JM; Kim SJ; Ostmo S; Chan RVP; Dy J; Erdogmus D; Ioannidis S; Kalpathy-Cramer J; Chiang MF;
Br J Ophthalmol; 2018 Nov; ():. PubMed ID: 30470715
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Performance of deep-learning artificial intelligence algorithms in detecting retinopathy of prematurity: A systematic review.
Bai A; Carty C; Dai S
Saudi J Ophthalmol; 2022; 36(3):296-307. PubMed ID: 36276252
[TBL] [Abstract][Full Text] [Related]
24. Multicenter Validation of Deep Learning Algorithm ROP.AI for the Automated Diagnosis of Plus Disease in ROP.
Bai A; Dai S; Hung J; Kirpalani A; Russell H; Elder J; Shah S; Carty C; Tan Z
Transl Vis Sci Technol; 2023 Aug; 12(8):13. PubMed ID: 37578427
[TBL] [Abstract][Full Text] [Related]
25. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
Gulshan V; Peng L; Coram M; Stumpe MC; Wu D; Narayanaswamy A; Venugopalan S; Widner K; Madams T; Cuadros J; Kim R; Raman R; Nelson PC; Mega JL; Webster DR
JAMA; 2016 Dec; 316(22):2402-2410. PubMed ID: 27898976
[TBL] [Abstract][Full Text] [Related]
26. DIAROP: Automated Deep Learning-Based Diagnostic Tool for Retinopathy of Prematurity.
Attallah O
Diagnostics (Basel); 2021 Nov; 11(11):. PubMed ID: 34829380
[TBL] [Abstract][Full Text] [Related]
27. 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]
28. Convolutional Neural Network Based on Fluorescein Angiography Images for Retinopathy of Prematurity Management.
Lepore D; Ji MH; Pagliara MM; Lenkowicz J; Capocchiano ND; Tagliaferri L; Boldrini L; Valentini V; Damiani A;
Transl Vis Sci Technol; 2020 Jul; 9(2):37. PubMed ID: 32855841
[TBL] [Abstract][Full Text] [Related]
29. Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.
Campbell JP; Singh P; Redd TK; Brown JM; Shah PK; Subramanian P; Rajan R; Valikodath N; Cole E; Ostmo S; Chan RVP; Venkatapathy N; Chiang MF; Kalpathy-Cramer J
Pediatrics; 2021 Mar; 147(3):. PubMed ID: 33637645
[TBL] [Abstract][Full Text] [Related]
30. An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity.
Liu Y; Du Y; Wang X; Zhao X; Zhang S; Yu Z; Wu Z; Ntentakis DP; Tian R; Chen Y; Wang C; Yao X; Li R; Heng PA; Zhang G
Asia Pac J Ophthalmol (Phila); 2023 Sep-Oct 01; 12(5):468-476. PubMed ID: 37851564
[TBL] [Abstract][Full Text] [Related]
31. Automated Analysis for Retinopathy of Prematurity by Deep Neural Networks.
Hu J; Chen Y; Zhong J; Ju R; Yi Z
IEEE Trans Med Imaging; 2019 Jan; 38(1):269-279. PubMed ID: 30080144
[TBL] [Abstract][Full Text] [Related]
32. Image harmonization and deep learning automated classification of plus disease in retinopathy of prematurity.
Subramaniam A; Orge F; Douglass M; Can B; Monteoliva G; Fried E; Schbib V; Saidman G; Peña B; Ulacia S; Acevedo P; Rollins AM; Wilson DL
J Med Imaging (Bellingham); 2023 Nov; 10(6):061107. PubMed ID: 37794884
[TBL] [Abstract][Full Text] [Related]
33. Automatic Staging for Retinopathy of Prematurity With Deep Feature Fusion and Ordinal Classification Strategy.
Peng Y; Zhu W; Chen Z; Wang M; Geng L; Yu K; Zhou Y; Wang T; Xiang D; Chen F; Chen X
IEEE Trans Med Imaging; 2021 Jul; 40(7):1750-1762. PubMed ID: 33710954
[TBL] [Abstract][Full Text] [Related]
34. 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]
35. Plus Disease in Telemedicine Approaches to Evaluating Acute-Phase ROP (e-ROP) Study: Characteristics, Predictors, and Accuracy of Image Grading.
Cheng QE; Daniel E; Pan W; Baumritter A; Quinn GE; Ying GS;
Ophthalmology; 2019 Jun; 126(6):868-875. PubMed ID: 30690127
[TBL] [Abstract][Full Text] [Related]
36. 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]
37. Automated retinopathy of prematurity screening using deep neural networks.
Wang J; Ju R; Chen Y; Zhang L; Hu J; Wu Y; Dong W; Zhong J; Yi Z
EBioMedicine; 2018 Sep; 35():361-368. PubMed ID: 30166272
[TBL] [Abstract][Full Text] [Related]
38. Artificial intelligence for the diagnosis of retinopathy of prematurity: A systematic review of current algorithms.
Ramanathan A; Athikarisamy SE; Lam GC
Eye (Lond); 2023 Aug; 37(12):2518-2526. PubMed ID: 36577806
[TBL] [Abstract][Full Text] [Related]
39. Automated Identification of Diabetic Retinopathy Using Deep Learning.
Gargeya R; Leng T
Ophthalmology; 2017 Jul; 124(7):962-969. PubMed ID: 28359545
[TBL] [Abstract][Full Text] [Related]
40. Automated Detection and Classification of Telemedical Retinopathy of Prematurity Images.
Vijayalakshmi C; Sakthivel P; Vinekar A
Telemed J E Health; 2020 Mar; 26(3):354-358. PubMed ID: 31084534
[No Abstract] [Full Text] [Related]
[Previous] [Next] [New Search]
