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Assessment Of Exercise Stress Testing With Artificial Neural Network In Determining Coronary Artery Disease And Predicting Lesion Localization

机译:人工神经网络对运动压力测试的评估,以确定冠状动脉疾病和预测病变部位

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The aim of this study is to show the artificial neural network (ANN) on determination of coronary artery disease existence and localization of lesion based upon exercise stress testing (EST) data.EST and coronary angiography were performed on 330 patients.The data studied acquiring 27 verifying features was normalized employing z-score method.To select training and test data,10-fold cross-validation methods were involved and multi-layered perceptron neural network was employed for the classification.The interpretation of EST using ANN proved 91%,73% and 65% diagnostic accuracy for the left main coronary (LMCA),left anterior descending and left circumflex coronary arteries,respectively.Besides.69% for the right coronary artery is also predicted.For the LMCA,a 94% negative predictive value (NPV) was obtained.This high percentage of NPV encourages the elimination of LMCA lesions.Some knowledge can also be obtained about lesion localization,besides diagnosing of coronary artery disease by the assessment of EST via ANN.
机译:这项研究的目的是展示基于运动压力测试(EST)数据的人工神经网络(ANN)用于确定冠状动脉疾病的存在和病变的位置.330例患者进行了EST和冠状动脉造影检查。使用z评分方法对27个验证特征进行了归一化。选择训练和测试数据,使用10倍交叉验证方法,并使用多层感知器神经网络进行分类。使用ANN的EST解释证明了91%,左主冠状动脉(LMCA),左前降支和左旋支冠状动脉的诊断准确率分别为73%和93%(右冠状动脉)阴性预测值(94%) (NPV)。如此高的NPV有助于消除LMCA病变。除了通过CT诊断冠状动脉疾病外,还可获得有关病变定位的一些知识。通过ANN对EST进行评估。

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