Abstract
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). 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. We suggest that the implementation of a bi-modal PDF will save test time and retain test accuracy.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Australian and New Zealand Journal of Ophthalmology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
