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An Efficient Deep Neural Network Multilayer Perceptron Based Classifier in Healthcare System

机译:医疗保健系统中有效的深神经网络多层Perceptron分类器

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The amount of data being stored in various repositories has been growing rapidly. In order to uncover hidden information from such data, there is a need for information extraction techniques. This resulted in the use of Data Mining and Machine Learning tasks such as Classification. One among the industries producing huge number of records on a daily basis is the Healthcare system. Data associated with medical field deal with the diagnosis of patients, higher accuracy in decision making is expected. In this work, we deal with the analysis of Cleveland Heart Disease data which contains 303 instances of patients records. Four classifiers are applied on the processed data to measure the accuracy of classification. Our results show that Deep Neural Net MLP classifier is able to diagnose the status of a patient with more accuracy.
机译:存储在各种存储库中的数据量迅速增长。为了从这些数据中揭示隐藏信息,需要信息提取技术。这导致使用数据挖掘和机器学习任务,例如分类。在每天生产大量记录的行业中是医疗保健系统。与医疗领域与诊断诊断相关的数据,预计决策的更高准确性。在这项工作中,我们处理克利夫兰心脏病数据分析,其中包含303例患者记录。在处理数据上应用四个分类器以测量分类的准确性。我们的研究结果表明,深度神经网络MLP分类器能够以更准确度诊断患者的状态。

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