These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

944 related items for PubMed ID: 29506863

  • 1. Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.
    Li Z, He Y, Keel S, Meng W, Chang RT, He M.
    Ophthalmology; 2018 Aug; 125(8):1199-1206. PubMed ID: 29506863
    [Abstract] [Full Text] [Related]

  • 2. 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
    [Abstract] [Full Text] [Related]

  • 3. Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.
    Li F, Yan L, Wang Y, Shi J, Chen H, Zhang X, Jiang M, Wu Z, Zhou K.
    Graefes Arch Clin Exp Ophthalmol; 2020 Apr; 258(4):851-867. PubMed ID: 31989285
    [Abstract] [Full Text] [Related]

  • 4. 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 01; 137(12):1353-1360. PubMed ID: 31513266
    [Abstract] [Full Text] [Related]

  • 5. Artificial intelligence in glaucoma detection using color fundus photographs.
    Sidhu Z, Mansoori T.
    Indian J Ophthalmol; 2024 Mar 01; 72(3):408-411. PubMed ID: 38099383
    [Abstract] [Full Text] [Related]

  • 6. Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.
    Yang HK, Kim YJ, Sung JY, Kim DH, Kim KG, Hwang JM.
    Am J Ophthalmol; 2020 Aug 01; 216():140-146. PubMed ID: 32247778
    [Abstract] [Full Text] [Related]

  • 7.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 8. Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.
    Jammal AA, Thompson AC, Mariottoni EB, Berchuck SI, Urata CN, Estrela T, Wakil SM, Costa VP, Medeiros FA.
    Am J Ophthalmol; 2020 Mar 01; 211():123-131. PubMed ID: 31730838
    [Abstract] [Full Text] [Related]

  • 9.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 10.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 11.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 12. A Deep Learning-Based Algorithm Identifies Glaucomatous Discs Using Monoscopic Fundus Photographs.
    Liu S, Graham SL, Schulz A, Kalloniatis M, Zangerl B, Cai W, Gao Y, Chua B, Arvind H, Grigg J, Chu D, Klistorner A, You Y.
    Ophthalmol Glaucoma; 2018 Mar 01; 1(1):15-22. PubMed ID: 32672627
    [Abstract] [Full Text] [Related]

  • 13. 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 Mar 01; 15(5):e0233079. PubMed ID: 32407355
    [Abstract] [Full Text] [Related]

  • 14. 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 01; 48(9):857-863. PubMed ID: 37246918
    [Abstract] [Full Text] [Related]

  • 15. An objective structural and functional reference standard in glaucoma.
    Mariottoni EB, Jammal AA, Berchuck SI, Shigueoka LS, Tavares IM, Medeiros FA.
    Sci Rep; 2021 Jan 18; 11(1):1752. PubMed ID: 33462288
    [Abstract] [Full Text] [Related]

  • 16. Intraocular Pressure and Glaucomatous Optic Neuropathy in High Myopia.
    Jonas JB, Nagaoka N, Fang YX, Weber P, Ohno-Matsui K.
    Invest Ophthalmol Vis Sci; 2017 Nov 01; 58(13):5897-5906. PubMed ID: 29164230
    [Abstract] [Full Text] [Related]

  • 17. 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 13; 316(22):2402-2410. PubMed ID: 27898976
    [Abstract] [Full Text] [Related]

  • 18. Assessing the Efficacy of Synthetic Optic Disc Images for Detecting Glaucomatous Optic Neuropathy Using Deep Learning.
    Chaurasia AK, MacGregor S, Craig JE, Mackey DA, Hewitt AW.
    Transl Vis Sci Technol; 2024 Jun 03; 13(6):1. PubMed ID: 38829624
    [Abstract] [Full Text] [Related]

  • 19. 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 03; 47(8):1009-1018. PubMed ID: 31215760
    [Abstract] [Full Text] [Related]

  • 20. Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs.
    Chakrabarty L, Joshi GD, Chakravarty A, Raman GV, Krishnadas SR, Sivaswamy J.
    J Glaucoma; 2016 Jul 03; 25(7):590-7. PubMed ID: 26580479
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 48.