Verbal classification in determining the intraocular pressure altitudes concerning the variation of central corneal thickness

Abstract

Precise intraocular pressure (IOP) measurement is the problem of the main importance in daily ophthalmologist practice. Identification of disturbing factors via artificial neural networks is the apropos alternative aiming to reduce measured IOP errors. The particular study base upon the construction of verbal algorithm with a purpose to minimize the measured IOP errors concerning Central corneal thickness (CCT) altitudes. To assess the relative risk for IOP error estimation artificial neural networks should be applied; i. e. for classification purpose to idenntify IOP eror via GAT for particular subject.