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

机译:基于自组织图数据分类的人工晶状体公式的选择

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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.
机译:在本文中,提出了一种使用自组织映射(SOM)从三种类型的人工晶状体(IOL)功率公式中选择一种用于每个白内障患者数据的方法。所提出的方法使用三维矢量,每个三维矢量具有轴向长度,角膜屈光力和圆柱度的测量值作为地图的训练数据。前两个值被替换为幂公式,而最后一个值与散光相关。本文还提出了神经元标记,该标记取决于在应用三个屈光力公式中的每一个的假设下发生的术后屈光不正。所提出的方法确定了适用于某些患者的公式,并通过与患者相关联的上述三个元素值来观察所显示数据的获胜者神经元上的标签。实验结果最终证明,所提出的方法足以有效地选择公式。

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