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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

101 related articles for article (PubMed ID: 8759263)

  • 1. Spatial classification of glaucomatous visual field loss.
    Henson DB; Spenceley SE; Bull DR
    Br J Ophthalmol; 1996 Jun; 80(6):526-31. PubMed ID: 8759263
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Artificial neural network analysis of noisy visual field data in glaucoma.
    Henson DB; Spenceley SE; Bull DR
    Artif Intell Med; 1997 Jun; 10(2):99-113. PubMed ID: 9201381
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Clinical use of a new method for visual field damage classification in glaucoma.
    Brusini P
    Eur J Ophthalmol; 1996; 6(4):402-7. PubMed ID: 8997583
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Inter-eye comparison of patterns of visual field loss in patients with glaucomatous optic neuropathy.
    Hoffmann EM; Boden C; Zangwill LM; Bourne RR; Weinreb RN; Sample PA
    Am J Ophthalmol; 2006 Apr; 141(4):703-8. PubMed ID: 16564806
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Oculokinetic perimetry compared with Humphrey visual field analysis in the detection of glaucomatous visual field loss.
    Wishart PK
    Eye (Lond); 1993; 7 ( Pt 1)():113-21. PubMed ID: 8325400
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Glaucoma diagnostics.
    Geimer SA
    Acta Ophthalmol; 2013 Feb; 91 Thesis 1():1-32. PubMed ID: 23384049
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Recognizing glaucomatous field loss with the Humphrey STATPAC.
    Enger C; Sommer A
    Arch Ophthalmol; 1987 Oct; 105(10):1355-7. PubMed ID: 3662906
    [TBL] [Abstract][Full Text] [Related]  

  • 8. The groningen longitudinal glaucoma study III. The predictive value of frequency-doubling perimetry and GDx nerve fibre analyser test results for the development of glaucomatous visual field loss.
    Heeg GP; Jansonius NM
    Eye (Lond); 2009 Aug; 23(8):1647-52. PubMed ID: 19011607
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparison of clinicians and an artificial neural network regarding accuracy and certainty in performance of visual field assessment for the diagnosis of glaucoma.
    Andersson S; Heijl A; Bizios D; Bengtsson B
    Acta Ophthalmol; 2013 Aug; 91(5):413-7. PubMed ID: 22583841
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Trained artificial neural network for glaucoma diagnosis using visual field data: a comparison with conventional algorithms.
    Bizios D; Heijl A; Bengtsson B
    J Glaucoma; 2007 Jan; 16(1):20-8. PubMed ID: 17224745
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Glaucomatous visual loss: field, color, and contrast.
    Drake MV
    Int Ophthalmol Clin; 1990; 30(3):169-76. PubMed ID: 2199386
    [No Abstract]   [Full Text] [Related]  

  • 12. Do pattern deviation values accurately estimate glaucomatous visual field damage in eyes with glaucoma and cataract?
    Matsuda A; Hara T; Miyata K; Matsuo H; Murata H; Mayama C; Asaoka R
    Br J Ophthalmol; 2015 Sep; 99(9):1240-4. PubMed ID: 25795915
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Evaluation of a Novel Visual Field Analyzer Application for Automated Classification of Glaucoma Severity.
    Germano RAS; de Moraes CG; Susanna R; Dantas DO; Neto EDS
    J Glaucoma; 2017 Jun; 26(6):586-591. PubMed ID: 28368999
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics.
    Thomas PBM; Chan T; Nixon T; Muthusamy B; White A
    Eye (Lond); 2019 Jul; 33(7):1133-1139. PubMed ID: 30833668
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Spatial changes of central field loss in diabetic retinopathy after laser.
    Wang Y; Muqit MM; Stanga PE; Young LB; Henson DB
    Optom Vis Sci; 2014 Jan; 91(1):111-20. PubMed ID: 24366435
    [TBL] [Abstract][Full Text] [Related]  

  • 16. New approach to estimating variability in visual field data using an image processing technique.
    Crabb DP; Edgar DF; Fitzke FW; McNaught AI; Wynn HP
    Br J Ophthalmol; 1995 Mar; 79(3):213-7. PubMed ID: 7703196
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Analysis of visual field progression in glaucoma.
    Fitzke FW; Hitchings RA; Poinoosawmy D; McNaught AI; Crabb DP
    Br J Ophthalmol; 1996 Jan; 80(1):40-8. PubMed ID: 8664231
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Choosing two points to add to the 24-2 pattern to better describe macular visual field damage due to glaucoma.
    Chen S; McKendrick AM; Turpin A
    Br J Ophthalmol; 2015 Sep; 99(9):1236-9. PubMed ID: 25802251
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrated visual fields: a new approach to measuring the binocular field of view and visual disability.
    Crabb DP; Viswanathan AC
    Graefes Arch Clin Exp Ophthalmol; 2005 Mar; 243(3):210-6. PubMed ID: 15806374
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Unsupervised learning with independent component analysis can identify patterns of glaucomatous visual field defects.
    Goldbaum MH
    Trans Am Ophthalmol Soc; 2005; 103():270-80. PubMed ID: 17057807
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.