BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

180 related articles for article (PubMed ID: 37304043)

  • 1. Machine Learning to Predict Response to Ranibizumab in Neovascular Age-Related Macular Degeneration.
    Maunz A; Barras L; Kawczynski MG; Dai J; Lee AY; Spaide RF; Sahni J; Ferrara D
    Ophthalmol Sci; 2023 Dec; 3(4):100319. PubMed ID: 37304043
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration.
    Schmidt-Erfurth U; Bogunovic H; Sadeghipour A; Schlegl T; Langs G; Gerendas BS; Osborne A; Waldstein SM
    Ophthalmol Retina; 2018 Jan; 2(1):24-30. PubMed ID: 31047298
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine Learning to Predict Faricimab Treatment Outcome in Neovascular Age-Related Macular Degeneration.
    Kikuchi Y; Kawczynski MG; Anegondi N; Neubert A; Dai J; Ferrara D; Quezada-Ruiz C
    Ophthalmol Sci; 2024; 4(2):100385. PubMed ID: 37868796
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Subretinal Fluid Resolution and Visual Acuity in Patients with Neovascular Age-Related Macular Degeneration: A HARBOR Post Hoc Analysis.
    Lally DR; Hill L; Amador-Patarroyo MJ
    Ophthalmol Retina; 2022 Nov; 6(11):1054-1060. PubMed ID: 35654363
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting Incremental and Future Visual Change in Neovascular Age-Related Macular Degeneration Using Deep Learning.
    Fu DJ; Faes L; Wagner SK; Moraes G; Chopra R; Patel PJ; Balaskas K; Keenan TDL; Bachmann LM; Keane PA
    Ophthalmol Retina; 2021 Nov; 5(11):1074-1084. PubMed ID: 33516917
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Characteristics that Correlate with Macular Atrophy in Ranibizumab-Treated Patients with Neovascular Age-Related Macular Degeneration.
    Staurenghi G; Cozzi M; Sadda S; Hill L; Gune S
    Ophthalmol Retina; 2023 Apr; 7(4):300-306. PubMed ID: 36372347
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Macular neovascularization lesion type and vision outcomes in neovascular age-related macular degeneration: post hoc analysis of HARBOR.
    Freund KB; Staurenghi G; Jung JJ; Zweifel SA; Cozzi M; Hill L; Blotner S; Tsuboi M; Gune S
    Graefes Arch Clin Exp Ophthalmol; 2022 Aug; 260(8):2437-2447. PubMed ID: 35239009
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Spectral-Domain OCT-Based Prevalence and Progression of Macular Atrophy in the HARBOR Study for Neovascular Age-Related Macular Degeneration.
    Gune S; Abdelfattah NS; Karamat A; Balasubramanian S; Marion KM; Morgenthien E; Sadda SR
    Ophthalmology; 2020 Apr; 127(4):523-532. PubMed ID: 31718842
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Are Dilated Fundus Examinations Needed for OCT-Guided Retreatment of Exudative Age-Related Macular Degeneration?
    Patel Y; Miller DM; Fung AE; Hill LF; Rosenfeld PJ
    Ophthalmol Retina; 2020 Feb; 4(2):141-147. PubMed ID: 31735634
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Spectral-Domain OCT Analysis of Risk Factors for Macular Atrophy Development in the HARBOR Study for Neovascular Age-Related Macular Degeneration.
    Sadda SR; Abdelfattah NS; Lei J; Shi Y; Marion KM; Morgenthien E; Gune S; Balasubramanian S
    Ophthalmology; 2020 Oct; 127(10):1360-1370. PubMed ID: 32402555
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Outcomes by Baseline Choroidal Neovascularization Features in Age-Related Macular Degeneration: A Post Hoc Analysis of the VIEW Studies.
    Steinle NC; Du W; Gibson A; Saroj N
    Ophthalmol Retina; 2021 Feb; 5(2):141-150. PubMed ID: 32652314
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration.
    Rohm M; Tresp V; Müller M; Kern C; Manakov I; Weiss M; Sim DA; Priglinger S; Keane PA; Kortuem K
    Ophthalmology; 2018 Jul; 125(7):1028-1036. PubMed ID: 29454659
    [TBL] [Abstract][Full Text] [Related]  

  • 13. OCT-Derived Radiomic Features Predict Anti-VEGF Response and Durability in Neovascular Age-Related Macular Degeneration.
    Kar SS; Cetin H; Lunasco L; Le TK; Zahid R; Meng X; Srivastava SK; Madabhushi A; Ehlers JP
    Ophthalmol Sci; 2022 Dec; 2(4):100171. PubMed ID: 36531588
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Effect of Residual Retinal Fluid on Visual Function in Ranibizumab-Treated Neovascular Age-Related Macular Degeneration.
    Holekamp NM; Sadda S; Sarraf D; Guymer R; Hill L; Blotner S; Spicer G; Gune S
    Am J Ophthalmol; 2022 Jan; 233():8-17. PubMed ID: 34289338
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Timing of Peak Vision Gains in Patients with Neovascular Age-Related Macular Degeneration Treated with Ranibizumab.
    Khurana RN; Chang L; Day BM; Ghanekar A; Stoilov I
    Ophthalmol Retina; 2020 Aug; 4(8):760-766. PubMed ID: 32387055
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting treat-and-extend outcomes and treatment intervals in neovascular age-related macular degeneration from retinal optical coherence tomography using artificial intelligence.
    Bogunović H; Mares V; Reiter GS; Schmidt-Erfurth U
    Front Med (Lausanne); 2022; 9():958469. PubMed ID: 36017006
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Macular Atrophy in the HARBOR Study for Neovascular Age-Related Macular Degeneration.
    Sadda SR; Tuomi LL; Ding B; Fung AE; Hopkins JJ
    Ophthalmology; 2018 Jun; 125(6):878-886. PubMed ID: 29477692
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Twelve-month efficacy and safety of 0.5 mg or 2.0 mg ranibizumab in patients with subfoveal neovascular age-related macular degeneration.
    Busbee BG; Ho AC; Brown DM; Heier JS; Suñer IJ; Li Z; Rubio RG; Lai P;
    Ophthalmology; 2013 May; 120(5):1046-56. PubMed ID: 23352196
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Ranibizumab Treatment for Pigment Epithelial Detachment Secondary to Neovascular Age-Related Macular Degeneration: Post Hoc Analysis of the HARBOR Study.
    Sarraf D; London NJ; Khurana RN; Dugel PU; Gune S; Hill L; Tuomi L
    Ophthalmology; 2016 Oct; 123(10):2213-24. PubMed ID: 27566855
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Development of Deep Learning Models to Predict Best-Corrected Visual Acuity from Optical Coherence Tomography.
    Kawczynski MG; Bengtsson T; Dai J; Hopkins JJ; Gao SS; Willis JR
    Transl Vis Sci Technol; 2020 Sep; 9(2):51. PubMed ID: 32974088
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.