On Selection of Intraocular Power Formula Using Support Vector Machines and Genetic Algorithm

In this paper, selection of formulas to calculate intraocular lens (IOL) power is presented for a cataract patient, using support vector machines (SVM´s) and genetic algorithm (GA). Each of the used data belongs to one of the three classes specified by names of the power formulas. The proposed method addresses the formula selection as the issue of classifying the data associated with the patient. The formulas have variables into which values of axial length and corneal refractive power are substituted, and hence each of the data has elements associated with them. Other elements probably useful in classifying the data are determined by GA. The final discrimination model is constructed by SVM learning using the above data. It 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 experimental results establish that the proposed method achieves the substantial percentage of concordance for the classification.