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Designing an Artificial Neural Network model for the prediction of kidney problems symptom through patient's metal behavior for pre- clinical medical diagnostic

机译:通过患者的金属行为对临床医疗诊断预测肾脏问题预测的人工神经网络模型

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This paper contains a report on a very simple functional model of Artificial Neural Networks, the article is proposed to aid current pre-clinical patient diagnosis methods. The study investigated the use of Artificial Neural Networks in predicting the kidney problems symptom through comparing mental behavior of different patients. Images were taught to the network through the matrix algorithms we generated and implemented using Matlab software. We did testing on 10 samples, 2 for each case, which successfully identified each sample according to facial information trained to identify. This study demonstrate that the proposed approach could be used as method of patient for prediction of various diseases especially in provision of initial care for an illness.
机译:本文包含关于人工神经网络的一个非常简单的功能模型的报告,该文章提出了帮助当前临床前患者的诊断方法。 该研究通过比较不同患者的心理行为来研究人工神经网络在预测肾脏问题症状中。 通过我们使用MATLAB软件生成和实现的矩阵算法向网络教授图像。 我们在每种情况下进行10个样品,2个样品,该样本是根据培训的面部信息成功识别每个样本以识别。 本研究表明,该方法可用作患者的方法,以便预测各种疾病,特别是在为疾病提供初始护理。

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