Corneal Thickness Factor and Artificial Intelligent Control for Intraocular Pressure Estimation

Abstract

Estimation and valuation of confounding factors via artificial intelligent technologies is of the main importance when eliminating intraocular pressure tonometric mistakes. Current investigation focuses on intraocular pressure (IOP) magnitude, being the basis in diagnosis and monitoring of ocular hypertension, valuation reliability. The statistical modeling of experimental data, proved the central corneal thickness (CCT) to be confounding factor and positively correlated source of variation in intraocular pressure measurements among ocular hypertension subjects. To fix reliability of measured intraocular pressure magnitudes the artificial intelligent control in terms of numerical simulations via finite element method is proposed. Referring to statistical modeling of experimental data and provided numerical simulations in general conclusion we point the imperative of the artificial intelligent control method applied for introduce of CCT correction factor when having measured IOP via GAT. The convergence of proposed artificial intelligent control method proves it to be an appropriate alternative for ocular hypertension misdiagnose. Ill. 5, bibl. 3 (in English, summaries in Lithuanian, English, Russian).