On selection of intraocular power formula based on data classification using self-organizing maps

In this paper, a method of selecting one type out of three types of intraocular lens (IOL) power formulas for data of each individual cataract patient is presented, using self-organizing maps (SOM´s). The proposed method employs three-dimensional vectors each of which has measured values of axial length, corneal refractive power and cylinder as training data for maps. The first two values are substituted into the power formulas, while the last value is associated with the astigmatism. This paper also proposes neuron labeling that depends on postoperative refractive errors occurring under the assumption that each of the three power formulas is applied. The proposed method determines the formula to be applied to some patient, observing the label attached to the winner neuron for the presented data with the above three element values associated with the patient. The experimental results finally establish that the proposed method adequately works to select the formula.