184 related articles for article (PubMed ID: 36766451)
1. A Survey on Deep-Learning-Based Diabetic Retinopathy Classification.
Sebastian A; Elharrouss O; Al-Maadeed S; Almaadeed N
Diagnostics (Basel); 2023 Jan; 13(3):. PubMed ID: 36766451
[TBL] [Abstract][Full Text] [Related]
2. Diabetic retinopathy screening through artificial intelligence algorithms: A systematic review.
Farahat Z; Zrira N; Souissi N; Bennani Y; Bencherif S; Benamar S; Belmekki M; Ngote MN; Megdiche K
Surv Ophthalmol; 2024 Jun; ():. PubMed ID: 38885761
[TBL] [Abstract][Full Text] [Related]
3. Combining transfer learning with retinal lesion features for accurate detection of diabetic retinopathy.
Hassan D; Gill HM; Happe M; Bhatwadekar AD; Hajrasouliha AR; Janga SC
Front Med (Lausanne); 2022; 9():1050436. PubMed ID: 36425113
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. A systematic review on diabetic retinopathy detection and classification based on deep learning techniques using fundus images.
Bhulakshmi D; Rajput DS
PeerJ Comput Sci; 2024; 10():e1947. PubMed ID: 38699206
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.
Tsiknakis N; Theodoropoulos D; Manikis G; Ktistakis E; Boutsora O; Berto A; Scarpa F; Scarpa A; Fotiadis DI; Marias K
Comput Biol Med; 2021 Aug; 135():104599. PubMed ID: 34247130
[TBL] [Abstract][Full Text] [Related]
9. Review on diabetic retinopathy with deep learning methods.
Shekar S; Satpute N; Gupta A
J Med Imaging (Bellingham); 2021 Nov; 8(6):060901. PubMed ID: 34859116
[No Abstract] [Full Text] [Related]
10. 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]
11. Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy.
Le D; Alam M; Yao CK; Lim JI; Hsieh YT; Chan RVP; Toslak D; Yao X
Transl Vis Sci Technol; 2020 Jul; 9(2):35. PubMed ID: 32855839
[TBL] [Abstract][Full Text] [Related]
12. Diabetic Retinopathy Detection from Fundus Images of the Eye Using Hybrid Deep Learning Features.
Butt MM; Iskandar DNFA; Abdelhamid SE; Latif G; Alghazo R
Diagnostics (Basel); 2022 Jul; 12(7):. PubMed ID: 35885512
[TBL] [Abstract][Full Text] [Related]
13. Recent developments on computer aided systems for diagnosis of diabetic retinopathy: a review.
Dubey S; Dixit M
Multimed Tools Appl; 2023; 82(10):14471-14525. PubMed ID: 36185322
[TBL] [Abstract][Full Text] [Related]
14. Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey.
Lakshminarayanan V; Kheradfallah H; Sarkar A; Jothi Balaji J
J Imaging; 2021 Aug; 7(9):. PubMed ID: 34460801
[TBL] [Abstract][Full Text] [Related]
15. Deep learning algorithms for detection of diabetic retinopathy in retinal fundus photographs: A systematic review and meta-analysis.
Islam MM; Yang HC; Poly TN; Jian WS; Jack Li YC
Comput Methods Programs Biomed; 2020 Jul; 191():105320. PubMed ID: 32088490
[TBL] [Abstract][Full Text] [Related]
16. Simple methods for the lesion detection and severity grading of diabetic retinopathy by image processing and transfer learning.
Sugeno A; Ishikawa Y; Ohshima T; Muramatsu R
Comput Biol Med; 2021 Oct; 137():104795. PubMed ID: 34488028
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Diabetic Retinopathy Screening Using Artificial Intelligence and Handheld Smartphone-Based Retinal Camera.
Malerbi FK; Andrade RE; Morales PH; Stuchi JA; Lencione D; de Paulo JV; Carvalho MP; Nunes FS; Rocha RM; Ferraz DA; Belfort R
J Diabetes Sci Technol; 2022 May; 16(3):716-723. PubMed ID: 33435711
[TBL] [Abstract][Full Text] [Related]
19. Transfer Learning-Based Model for Diabetic Retinopathy Diagnosis Using Retinal Images.
Jabbar MK; Yan J; Xu H; Ur Rehman Z; Jabbar A
Brain Sci; 2022 Apr; 12(5):. PubMed ID: 35624922
[TBL] [Abstract][Full Text] [Related]
20. Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning.
Alyoubi WL; Abulkhair MF; Shalash WM
Sensors (Basel); 2021 May; 21(11):. PubMed ID: 34073541
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]