Evaluating a perimetric expert system experience with Octosmart

  • Hans-Peter Hirsbrunner
  • Franz Fankhauser
  • Alfred Jenni
  • Arthur Funkhouser
Clinical Investigations


When evaluating expert systems to be used in clinical perimetry, various aspects of their performance as compared with that of human interpreters must be considered. In this investigation, the results produced by the new Octosmart diagnostic program have been compared with the performance of three interpreters with various amounts of experience in visual field analysis. The evaluations were based on 27 visual fields with glaucomatous damage, which had been examined with the Octopus program GI. It is shown that in borderline cases (i.e., neither clearly normal nor clearly pathological) where strict statistical criteria must be employed in order to distinguish between possible pathology and artifacts, the “personal styles” of human interpreters, more than standardized decision criteria, implicitly guide the decision process, resulting in unpredictable, nonstandardized interindividual differences. A standardized expert system, based on constant, explicit, and logical criteria is therefore considered to be superior to unaided human interpretation. It is pointed out that the influence of the implicit decision criteria of human interpreters must be controlled carefully if expert systems are to be evaluated with reference to human interpreters.


Visual Field Expert System Decision Criterion Field Analysis Borderline Case 
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  1. 1.
    Armaly MF (1985) Automated versus manual perimetry. In: Whalen WR, Spaeth GL (eds) Computerized visual fields. Slack, Thorofare, N.J., pp 347–358Google Scholar
  2. 2.
    Bebie H (1990) Computer-assisted evaluation of visual fields. Graefe's Arch Clin Exp Ophthalmol 228:242–245Google Scholar
  3. 3.
    Fankhauser F, Koch P, Roulier A (1972) On automation of perimetry. Graefe's Arch Clin Exp Ophthalmol 184:126–150Google Scholar
  4. 4.
    Heijl A, Krakau CET (1975) An automatic perimeter for glaucoma visual field screening and control. Graefe's Arch Clin Exp Ophthalmol 197:13–23Google Scholar
  5. 5.
    Kaufmann H, Flammer J (1990) Evaluation of visual fields by ophthalmologists and by the Octosmart program (unpublished results)Google Scholar
  6. 6.
    LeBlanc RP (1985) Abnormal values in computerized perimetry. In: Whalen WR, Spaeth GL (eds) Computerized visual fields. Slack, Thorofare, N.J., pp 167–193Google Scholar
  7. 7.
    Niesel P (1970) Streuungen perimetrischer Untersuchungsergebnisse. Ophthalmologica 161:180–186Google Scholar
  8. 8.
    Schmied U (1979) Automatic (Octopus) and manual (Goldmann) perimetry in glaucoma: first experiences. Proc First Int Meeting on automated perimetry system Octopus, Interzeag AG, Schlieren, Switzerland, April 6/7, 1979Google Scholar
  9. 9.
    Stürmer J, Vollrath-Junger C, Lautenbach K, Gloor B (1988) Computerized visual field analysis. Poster, 8th Int Visual Field Symposium, Vancouver, May 9–12,1988Google Scholar

Copyright information

© Springer-Verlag 1990

Authors and Affiliations

  • Hans-Peter Hirsbrunner
    • 1
  • Franz Fankhauser
    • 1
  • Alfred Jenni
    • 1
  • Arthur Funkhouser
    • 1
  1. 1.Universitäts-AugenklinikBernSwitzerland

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