Background: Automated perimetry is associated with lengthy test times, but Baysean predictions can be applied to speed up testing. A critical component of such methods is the starting probability density function (PDF).
Methods/results: In the present study we show that a unimodal PDF, suggested n the literature as adequate for clinical data, fails to describe the thresholds of diseased eyes and we develop a bi-modal PDF representative of a clinical population.
Conclusion: We suggest that the implementation of a bi-modal PDF will save test time and retain test accuracy.