537 related articles for article (PubMed ID: 31606108)
1. Referable diabetic retinopathy identification from eye fundus images with weighted path for convolutional neural network.
Liu YP; Li Z; Xu C; Li J; Liang R
Artif Intell Med; 2019 Aug; 99():101694. PubMed ID: 31606108
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Bimodal learning via trilogy of skip-connection deep networks for diabetic retinopathy risk progression identification.
Hua CH; Huynh-The T; Kim K; Yu SY; Le-Tien T; Park GH; Bang J; Khan WA; Bae SH; Lee S
Int J Med Inform; 2019 Dec; 132():103926. PubMed ID: 31605882
[TBL] [Abstract][Full Text] [Related]
4. A convolutional neural network for the screening and staging of diabetic retinopathy.
Shaban M; Ogur Z; Mahmoud A; Switala A; Shalaby A; Abu Khalifeh H; Ghazal M; Fraiwan L; Giridharan G; Sandhu H; El-Baz AS
PLoS One; 2020; 15(6):e0233514. PubMed ID: 32569310
[TBL] [Abstract][Full Text] [Related]
5. Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.
Bellemo V; Lim ZW; Lim G; Nguyen QD; Xie Y; Yip MYT; Hamzah H; Ho J; Lee XQ; Hsu W; Lee ML; Musonda L; Chandran M; Chipalo-Mutati G; Muma M; Tan GSW; Sivaprasad S; Menon G; Wong TY; Ting DSW
Lancet Digit Health; 2019 May; 1(1):e35-e44. PubMed ID: 33323239
[TBL] [Abstract][Full Text] [Related]
6. Diabetic retinopathy classification based on multipath CNN and machine learning classifiers.
Gayathri S; Gopi VP; Palanisamy P
Phys Eng Sci Med; 2021 Sep; 44(3):639-653. PubMed ID: 34033015
[TBL] [Abstract][Full Text] [Related]
7. Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey.
Asiri N; Hussain M; Al Adel F; Alzaidi N
Artif Intell Med; 2019 Aug; 99():101701. PubMed ID: 31606116
[TBL] [Abstract][Full Text] [Related]
8. An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs.
Li Z; Keel S; Liu C; He Y; Meng W; Scheetz J; Lee PY; Shaw J; Ting D; Wong TY; Taylor H; Chang R; He M
Diabetes Care; 2018 Dec; 41(12):2509-2516. PubMed ID: 30275284
[TBL] [Abstract][Full Text] [Related]
9. Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.
Wang XN; Dai L; Li ST; Kong HY; Sheng B; Wu Q
Curr Eye Res; 2020 Dec; 45(12):1550-1555. PubMed ID: 32410471
[No Abstract] [Full Text] [Related]
10. Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy - Artificial intelligence versus clinician for screening.
Shah P; Mishra DK; Shanmugam MP; Doshi B; Jayaraj H; Ramanjulu R
Indian J Ophthalmol; 2020 Feb; 68(2):398-405. PubMed ID: 31957737
[TBL] [Abstract][Full Text] [Related]
11. Non-uniform Label Smoothing for Diabetic Retinopathy Grading from Retinal Fundus Images with Deep Neural Networks.
Galdran A; Chelbi J; Kobi R; Dolz J; Lombaert H; Ben Ayed I; Chakor H
Transl Vis Sci Technol; 2020 Jun; 9(2):34. PubMed ID: 32832207
[TBL] [Abstract][Full Text] [Related]
12. Deep learning assisted detection of glaucomatous optic neuropathy and potential designs for a generalizable model.
Ko YC; Wey SY; Chen WT; Chang YF; Chen MJ; Chiou SH; Liu CJ; Lee CY
PLoS One; 2020; 15(5):e0233079. PubMed ID: 32407355
[TBL] [Abstract][Full Text] [Related]
13. Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading.
Sahlsten J; Jaskari J; Kivinen J; Turunen L; Jaanio E; Hietala K; Kaski K
Sci Rep; 2019 Jul; 9(1):10750. PubMed ID: 31341220
[TBL] [Abstract][Full Text] [Related]
14. Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning.
Abràmoff MD; Lou Y; Erginay A; Clarida W; Amelon R; Folk JC; Niemeijer M
Invest Ophthalmol Vis Sci; 2016 Oct; 57(13):5200-5206. PubMed ID: 27701631
[TBL] [Abstract][Full Text] [Related]
15. Effective methods of diabetic retinopathy detection based on deep convolutional neural networks.
Gu Y; Wang X; Pan J; Yong Z; Guo S; Pan T; Jiao Y; Zhou Z
Int J Comput Assist Radiol Surg; 2021 Dec; 16(12):2177-2187. PubMed ID: 34606059
[TBL] [Abstract][Full Text] [Related]
16. Deep Learning-Based Algorithms in Screening of Diabetic Retinopathy: A Systematic Review of Diagnostic Performance.
Nielsen KB; Lautrup ML; Andersen JKH; Savarimuthu TR; Grauslund J
Ophthalmol Retina; 2019 Apr; 3(4):294-304. PubMed ID: 31014679
[TBL] [Abstract][Full Text] [Related]
17. Diabetic retinopathy detection using red lesion localization and convolutional neural networks.
Zago GT; Andreão RV; Dorizzi B; Teatini Salles EO
Comput Biol Med; 2020 Jan; 116():103537. PubMed ID: 31747632
[TBL] [Abstract][Full Text] [Related]
18. Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy.
Tseng VS; Chen CL; Liang CM; Tai MC; Liu JT; Wu PY; Deng MS; Lee YW; Huang TY; Chen YH
Transl Vis Sci Technol; 2020 Jul; 9(2):41. PubMed ID: 32855845
[TBL] [Abstract][Full Text] [Related]
19. Fundus photograph-based deep learning algorithms in detecting diabetic retinopathy.
Raman R; Srinivasan S; Virmani S; Sivaprasad S; Rao C; Rajalakshmi R
Eye (Lond); 2019 Jan; 33(1):97-109. PubMed ID: 30401899
[TBL] [Abstract][Full Text] [Related]
20. Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.
Xu K; Feng D; Mi H
Molecules; 2017 Nov; 22(12):. PubMed ID: 29168750
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]