313 related articles for article (PubMed ID: 35902186)
1. Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study.
Zhang G; Lin JW; Wang J; Ji J; Cen LP; Chen W; Xie P; Zheng Y; Xiong Y; Wu H; Li D; Ng TK; Pang CP; Zhang M
BMJ Open; 2022 Jul; 12(7):e060155. PubMed ID: 35902186
[TBL] [Abstract][Full Text] [Related]
2. Performance of Automated Machine Learning for Diabetic Retinopathy Image Classification from Multi-field Handheld Retinal Images.
Jacoba CMP; Doan D; Salongcay RP; Aquino LAC; Silva JPY; Salva CMG; Zhang D; Alog GP; Zhang K; Locaylocay KLRB; Saunar AV; Ashraf M; Sun JK; Peto T; Aiello LP; Silva PS
Ophthalmol Retina; 2023 Aug; 7(8):703-712. PubMed ID: 36924893
[TBL] [Abstract][Full Text] [Related]
3. Detection of Diabetic Retinopathy from Ultra-Widefield Scanning Laser Ophthalmoscope Images: A Multicenter Deep Learning Analysis.
Tang F; Luenam P; Ran AR; Quadeer AA; Raman R; Sen P; Khan R; Giridhar A; Haridas S; Iglicki M; Zur D; Loewenstein A; Negri HP; Szeto S; Lam BKY; Tham CC; Sivaprasad S; Mckay M; Cheung CY
Ophthalmol Retina; 2021 Nov; 5(11):1097-1106. PubMed ID: 33540169
[TBL] [Abstract][Full Text] [Related]
4. Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration.
González-Gonzalo C; Sánchez-Gutiérrez V; Hernández-Martínez P; Contreras I; Lechanteur YT; Domanian A; van Ginneken B; Sánchez CI
Acta Ophthalmol; 2020 Jun; 98(4):368-377. PubMed ID: 31773912
[TBL] [Abstract][Full Text] [Related]
5. Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.
Wang J; Ji J; Zhang M; Lin JW; Zhang G; Gong W; Cen LP; Lu Y; Huang X; Huang D; Li T; Ng TK; Pang CP
JAMA Netw Open; 2021 May; 4(5):e218758. PubMed ID: 33950206
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.
Ting DSW; Cheung CY; Lim G; Tan GSW; Quang ND; Gan A; Hamzah H; Garcia-Franco R; San Yeo IY; Lee SY; Wong EYM; Sabanayagam C; Baskaran M; Ibrahim F; Tan NC; Finkelstein EA; Lamoureux EL; Wong IY; Bressler NM; Sivaprasad S; Varma R; Jonas JB; He MG; Cheng CY; Cheung GCM; Aung T; Hsu W; Lee ML; Wong TY
JAMA; 2017 Dec; 318(22):2211-2223. PubMed ID: 29234807
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. In-Person Verification of Deep Learning Algorithm for Diabetic Retinopathy Screening Using Different Techniques Across Fundus Image Devices.
Wongchaisuwat N; Trinavarat A; Rodanant N; Thoongsuwan S; Phasukkijwatana N; Prakhunhungsit S; Preechasuk L; Wongchaisuwat P
Transl Vis Sci Technol; 2021 Nov; 10(13):17. PubMed ID: 34767624
[TBL] [Abstract][Full Text] [Related]
10. Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.
Wang Y; Yu M; Hu B; Jin X; Li Y; Zhang X; Zhang Y; Gong D; Wu C; Zhang B; Yang J; Li B; Yuan M; Mo B; Wei Q; Zhao J; Ding D; Yang J; Li X; Yu W; Chen Y
Diabetes Metab Res Rev; 2021 May; 37(4):e3445. PubMed ID: 33713564
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Combined automated screening for age-related macular degeneration and diabetic retinopathy in primary care settings.
Bhuiyan A; Govindaiah A; Alauddin S; Otero-Marquez O; Smith RT
Ann Eye Sci; 2021 Jun; 6():. PubMed ID: 34671718
[TBL] [Abstract][Full Text] [Related]
13. Automated image curation in diabetic retinopathy screening using deep learning.
Nderitu P; Nunez do Rio JM; Webster ML; Mann SS; Hopkins D; Cardoso MJ; Modat M; Bergeles C; Jackson TL
Sci Rep; 2022 Jul; 12(1):11196. PubMed ID: 35778615
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration.
Burlina PM; Joshi N; Pacheco KD; Liu TYA; Bressler NM
JAMA Ophthalmol; 2019 Mar; 137(3):258-264. PubMed ID: 30629091
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.
Li N; Ma M; Lai M; Gu L; Kang M; Wang Z; Jiao S; Dang K; Deng J; Ding X; Zhen Q; Zhang A; Shen T; Zheng Z; Wang Y; Peng Y
J Diabetes; 2022 Feb; 14(2):111-120. PubMed ID: 34889059
[TBL] [Abstract][Full Text] [Related]
18. Prediction of retinopathy progression using deep learning on retinal images within the Scottish screening programme.
Mellor J; Jiang W; Fleming A; McGurnaghan SJ; Blackbourn LAK; Styles C; Storkey A; McKeigue PM; Colhoun HM
Br J Ophthalmol; 2024 May; 108(6):833-839. PubMed ID: 38316534
[TBL] [Abstract][Full Text] [Related]
19. Deep learning for gradability classification of handheld, non-mydriatic retinal images.
Nderitu P; do Rio JMN; Rasheed R; Raman R; Rajalakshmi R; Bergeles C; Sivaprasad S;
Sci Rep; 2021 May; 11(1):9469. PubMed ID: 33947946
[TBL] [Abstract][Full Text] [Related]
20. A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography.
Ryu G; Lee K; Park D; Park SH; Sagong M
Sci Rep; 2021 Nov; 11(1):23024. PubMed ID: 34837030
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
