232 related articles for article (PubMed ID: 30409338)
1. SCREEN-DR: Collaborative platform for diabetic retinopathy.
Pedrosa M; Silva JM; Silva JF; Matos S; Costa C
Int J Med Inform; 2018 Dec; 120():137-146. PubMed ID: 30409338
[TBL] [Abstract][Full Text] [Related]
2. SCREEN-DR - Software Architecture for the Diabetic Retinopathy Screening.
Pedrosa M; Silva JM; Matos S; Costa C
Stud Health Technol Inform; 2018; 247():396-400. PubMed ID: 29677990
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.
S K S; P A
J Med Syst; 2017 Nov; 41(12):201. PubMed ID: 29124453
[TBL] [Abstract][Full Text] [Related]
6. Efficient multi-kernel multi-instance learning using weakly supervised and imbalanced data for diabetic retinopathy diagnosis.
Cao P; Ren F; Wan C; Yang J; Zaiane O
Comput Med Imaging Graph; 2018 Nov; 69():112-124. PubMed ID: 30237145
[TBL] [Abstract][Full Text] [Related]
7. Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System.
van der Heijden AA; Abramoff MD; Verbraak F; van Hecke MV; Liem A; Nijpels G
Acta Ophthalmol; 2018 Feb; 96(1):63-68. PubMed ID: 29178249
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.
Sosale B; Sosale AR; Murthy H; Sengupta S; Naveenam M
Indian J Ophthalmol; 2020 Feb; 68(2):391-395. PubMed ID: 31957735
[TBL] [Abstract][Full Text] [Related]
10. Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.
Gilbert MJ; Sun JK
Semin Ophthalmol; 2020 Nov; 35(7-8):325-332. PubMed ID: 33539253
[No Abstract] [Full Text] [Related]
11. A review on computer-aided recent developments for automatic detection of diabetic retinopathy.
Randive SN; Senapati RK; Rahulkar AD
J Med Eng Technol; 2019 Feb; 43(2):87-99. PubMed ID: 31198073
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Simple methods for segmentation and measurement of diabetic retinopathy lesions in retinal fundus images.
Köse C; Sevik U; Ikibaş C; Erdöl H
Comput Methods Programs Biomed; 2012 Aug; 107(2):274-93. PubMed ID: 21757250
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.
Porwal P; Pachade S; Kokare M; Deshmukh G; Son J; Bae W; Liu L; Wang J; Liu X; Gao L; Wu T; Xiao J; Wang F; Yin B; Wang Y; Danala G; He L; Choi YH; Lee YC; Jung SH; Li Z; Sui X; Wu J; Li X; Zhou T; Toth J; Baran A; Kori A; Chennamsetty SS; Safwan M; Alex V; Lyu X; Cheng L; Chu Q; Li P; Ji X; Zhang S; Shen Y; Dai L; Saha O; Sathish R; Melo T; Araújo T; Harangi B; Sheng B; Fang R; Sheet D; Hajdu A; Zheng Y; Mendonça AM; Zhang S; Campilho A; Zheng B; Shen D; Giancardo L; Quellec G; Mériaudeau F
Med Image Anal; 2020 Jan; 59():101561. PubMed ID: 31671320
[TBL] [Abstract][Full Text] [Related]
16. A Survey on Intelligent Screening for Diabetic Retinopathy.
Dai YL; Zhu CZ; Shan X; Cheng ZZ; Zou BJ
Chin Med Sci J; 2019 Jun; 34(2):120-132. PubMed ID: 31315753
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Points of interest and visual dictionaries for automatic retinal lesion detection.
Rocha A; Carvalho T; Jelinek HF; Goldenstein S; Wainer J
IEEE Trans Biomed Eng; 2012 Aug; 59(8):2244-53. PubMed ID: 22665502
[TBL] [Abstract][Full Text] [Related]
19. Artificial intelligence for diabetic retinopathy screening: a review.
Grzybowski A; Brona P; Lim G; Ruamviboonsuk P; Tan GSW; Abramoff M; Ting DSW
Eye (Lond); 2020 Mar; 34(3):451-460. PubMed ID: 31488886
[TBL] [Abstract][Full Text] [Related]
20. IDx-DR for Diabetic Retinopathy Screening.
Savoy M
Am Fam Physician; 2020 Mar; 101(5):307-308. PubMed ID: 32109029
[No Abstract] [Full Text] [Related]
[Next] [New Search]
