BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

223 related articles for article (PubMed ID: 31773912)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. Cross-camera Performance of Deep Learning Algorithms to Diagnose Common Ophthalmic Diseases: A Comparative Study Highlighting Feasibility to Portable Fundus Camera Use.
    He S; Bulloch G; Zhang L; Xie Y; Wu W; He Y; Meng W; Shi D; He M
    Curr Eye Res; 2023 Sep; 48(9):857-863. PubMed ID: 37246918
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Simultaneous screening and classification of diabetic retinopathy and age-related macular degeneration based on fundus photos-a prospective analysis of the RetCAD system.
    Skevas C; Weindler H; Levering M; Engelberts J; van Grinsven M; Katz T
    Int J Ophthalmol; 2022; 15(12):1985-1993. PubMed ID: 36536981
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.
    Grassmann F; Mengelkamp J; Brandl C; Harsch S; Zimmermann ME; Linkohr B; Peters A; Heid IM; Palm C; Weber BHF
    Ophthalmology; 2018 Sep; 125(9):1410-1420. PubMed ID: 29653860
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Development and validation of a deep-learning algorithm for the detection of neovascular age-related macular degeneration from colour fundus photographs.
    Keel S; Li Z; Scheetz J; Robman L; Phung J; Makeyeva G; Aung K; Liu C; Yan X; Meng W; Guymer R; Chang R; He M
    Clin Exp Ophthalmol; 2019 Nov; 47(8):1009-1018. PubMed ID: 31215760
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning-based automated detection for diabetic retinopathy and diabetic macular oedema in retinal fundus photographs.
    Li F; Wang Y; Xu T; Dong L; Yan L; Jiang M; Zhang X; Jiang H; Wu Z; Zou H
    Eye (Lond); 2022 Jul; 36(7):1433-1441. PubMed ID: 34211137
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. 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]  

  • 17. 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]  

  • 18. Using deep leaning models to detect ophthalmic diseases: A comparative study.
    Li Z; Guo X; Zhang J; Liu X; Chang R; He M
    Front Med (Lausanne); 2023; 10():1115032. PubMed ID: 36936225
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Use of Deep Learning for Detailed Severity Characterization and Estimation of 5-Year Risk Among Patients With Age-Related Macular Degeneration.
    Burlina PM; Joshi N; Pacheco KD; Freund DE; Kong J; Bressler NM
    JAMA Ophthalmol; 2018 Dec; 136(12):1359-1366. PubMed ID: 30242349
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.