BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1180 related articles for article (PubMed ID: 31281057)

  • 1. Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.
    Son J; Shin JY; Kim HD; Jung KH; Park KH; Park SJ
    Ophthalmology; 2020 Jan; 127(1):85-94. PubMed ID: 31281057
    [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. Fully automated detection of retinal disorders by image-based deep learning.
    Li F; Chen H; Liu Z; Zhang X; Wu Z
    Graefes Arch Clin Exp Ophthalmol; 2019 Mar; 257(3):495-505. PubMed ID: 30610422
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.
    Bajwa MN; Malik MI; Siddiqui SA; Dengel A; Shafait F; Neumeier W; Ahmed S
    BMC Med Inform Decis Mak; 2019 Jul; 19(1):136. PubMed ID: 31315618
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis.
    Niemeijer M; van Ginneken B; Russell SR; Suttorp-Schulten MS; Abràmoff MD
    Invest Ophthalmol Vis Sci; 2007 May; 48(5):2260-7. PubMed ID: 17460289
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.
    Phene S; Dunn RC; Hammel N; Liu Y; Krause J; Kitade N; Schaekermann M; Sayres R; Wu DJ; Bora A; Semturs C; Misra A; Huang AE; Spitze A; Medeiros FA; Maa AY; Gandhi M; Corrado GS; Peng L; Webster DR
    Ophthalmology; 2019 Dec; 126(12):1627-1639. PubMed ID: 31561879
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. A deep learning system for detecting diabetic retinopathy across the disease spectrum.
    Dai L; Wu L; Li H; Cai C; Wu Q; Kong H; Liu R; Wang X; Hou X; Liu Y; Long X; Wen Y; Lu L; Shen Y; Chen Y; Shen D; Yang X; Zou H; Sheng B; Jia W
    Nat Commun; 2021 May; 12(1):3242. PubMed ID: 34050158
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Deep Learning Performance of Ultra-Widefield Fundus Imaging for Screening Retinal Lesions in Rural Locales.
    Cui T; Lin D; Yu S; Zhao X; Lin Z; Zhao L; Xu F; Yun D; Pang J; Li R; Xie L; Zhu P; Huang Y; Huang H; Hu C; Huang W; Liang X; Lin H
    JAMA Ophthalmol; 2023 Nov; 141(11):1045-1051. PubMed ID: 37856107
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.
    Liu H; Li L; Wormstone IM; Qiao C; Zhang C; Liu P; Li S; Wang H; Mou D; Pang R; Yang D; Zangwill LM; Moghimi S; Hou H; Bowd C; Jiang L; Chen Y; Hu M; Xu Y; Kang H; Ji X; Chang R; Tham C; Cheung C; Ting DSW; Wong TY; Wang Z; Weinreb RN; Xu M; Wang N
    JAMA Ophthalmol; 2019 Dec; 137(12):1353-1360. PubMed ID: 31513266
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep image mining for diabetic retinopathy screening.
    Quellec G; Charrière K; Boudi Y; Cochener B; Lamard M
    Med Image Anal; 2017 Jul; 39():178-193. PubMed ID: 28511066
    [TBL] [Abstract][Full Text] [Related]  

  • 14. From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.
    Medeiros FA; Jammal AA; Thompson AC
    Ophthalmology; 2019 Apr; 126(4):513-521. PubMed ID: 30578810
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.
    Xiao W; Huang X; Wang JH; Lin DR; Zhu Y; Chen C; Yang YH; Xiao J; Zhao LQ; Li JO; Cheung CY; Mise Y; Guo ZY; Du YF; Chen BB; Hu JX; Zhang K; Lin XS; Wen W; Liu YZ; Chen WR; Zhong YS; Lin HT
    Lancet Digit Health; 2021 Feb; 3(2):e88-e97. PubMed ID: 33509389
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Development of a deep residual learning algorithm to screen for glaucoma from fundus photography.
    Shibata N; Tanito M; Mitsuhashi K; Fujino Y; Matsuura M; Murata H; Asaoka R
    Sci Rep; 2018 Oct; 8(1):14665. PubMed ID: 30279554
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.
    Cen LP; Ji J; Lin JW; Ju ST; Lin HJ; Li TP; Wang Y; Yang JF; Liu YF; Tan S; Tan L; Li D; Wang Y; Zheng D; Xiong Y; Wu H; Jiang J; Wu Z; Huang D; Shi T; Chen B; Yang J; Zhang X; Luo L; Huang C; Zhang G; Huang Y; Ng TK; Chen H; Chen W; Pang CP; Zhang M
    Nat Commun; 2021 Aug; 12(1):4828. PubMed ID: 34376678
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.
    Asaoka R; Tanito M; Shibata N; Mitsuhashi K; Nakahara K; Fujino Y; Matsuura M; Murata H; Tokumo K; Kiuchi Y
    Ophthalmol Glaucoma; 2019; 2(4):224-231. PubMed ID: 32672542
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 59.