Ophthalmological Examination Determination Using Data Classification Based on Feedforward Neural Networks
Ophthalmological Examination Determination Using Data Classification Based on Feedforward Neural Networks
复制标题
基于前馈神经网络的数据分类眼科检查判定
DOI：
10.1109/smc.2018.00158
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Hitoshi Tabuchi
中科院分区：
文献类型：
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作者：
Shoji Morita; Naotake Kamiura;Teijiro Isokawa;Takayuki Yumoto;Aoi Emura;Tomohusa Yamauchi;Hitoshi Tabuchi
本文提出了一种利用前馈神经网络（简称NN）确定眼科门诊患者检查结果的方法。该决定是基于数据分类。提出的方法定义了四类眼科检查。它从门诊病人访谈纸上的手写句子中为神经网络训练和考试确定准备数据。以矩阵的形式准备一组训练数据。从句子中提取的单词被分配到矩阵列中，而每个表格（或其中的句子）被分配到矩阵行中。矩阵中的条目采用二进制值，表示提取的单词是否出现在工作表中的句子中。该方法还将门诊患者的年龄作为输入项。神经网络训练采用常规反向传播算法，以一行作为训练数据之一。训练后的神经网络有四个输出神经元，每个神经元的值都属于[0,1]的范围。要检查的数据类别是通过搜索输出层中出现最大值的神经元来确定的。实验结果表明，该方法比其他方法具有更高的一致性。
In this paper, a method of determining examinations is proposed for ophthalmologic outpatients, using feedforward neural network (NN for short). The determination is based on the data classification. The proposed method defines four classes of ophthalmologic examinations. It prepares data for NN training and examination determination from handwriting sentences in outpatients' interview sheets. A set of the training data is prepared in the form of a matrix. The words extracted from the sentences are assigned to the matrix columns, while each sheet (or sentences in it) is assigned to a matrix rows. Entries in the matrix takes binary values meaning whether extracted words appear in the sentences in the sheet. The proposed method also the ages of outpatients as entries. NN training is conducted according to the normal backpropagation algorithm using a row as one of the training data. The trained NN has four output neurons each of which takes the value belonging to the range [0, 1]. The class of data to be examined is determined by searching the neuron at which the largest value appears in the output layer. Experimental results comprehensively establish that the proposed method can achieve higher percentages of concordance than other methods.