Formula selection for intraocular power calculation using support vector machines and self-organizing maps

In this paper, methods of selecting formulas to calculate intraocular lens (IOL) power for a cataract patient are presented, using support vector machines (SVM´s) and self-organizing maps (SOM´s). Each of training data has measured values associated with axial length and corneal refractive power as element values. Three IOL power formulas have variables into which these values are substituted. The discrimination model constructed by SVM learning consists of three coordinate spaces having two regions corresponding to two formulas out of three. Each of the spaces provides a potential solution. The formula to be used for some patient is specified by a majority of the potential solutions. The SOM-based scheme determines the formula suitable to some patient, observing the label attached to the winner neuron for the presented data having the above element values associated with the patient. The experimental results finally establish that the proposed SVM-based scheme especially works well to select the formula.