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Application of multilayer perceptron neural networks and support vector machines in classification of healthcare data

机译：多层erceptron神经网络的应用和支持向量机在医疗数据分类中的应用

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摘要

A large volume of data is steadily produced by the healthcare industry on daily basis. Data mining and machine learning approaches are two effective techniques applicable for data analysis and finding the hidden patterns which can be utilized for medical decision making. As the decisions in medical field are dealing with patient outcome, a high level of accuracy in data mining is needed. In this paper a comparison between implemented multilayer perceptron neural networks and support vector machine on heart diseases dataset is conducted. We have analyzed the effectiveness of support vector machine in classification, using a dataset of 303 patients. Our results show that support vector machine is able to classify more accurately.

机译：医疗保健行业每天稳定地生产大量数据。数据挖掘和机器学习方法是适用于数据分析的有效技术，并找到可用于医学决策的隐藏模式。随着医学领域的决定正在处理患者结果，需要高水平的数据挖掘精度。本文进行了在心脏病数据集中实现了多层的Multoneptron神经网络和支持向量机之间的比较。我们通过303名患者的数据集分析了支持向量机的有效性。我们的结果表明，支持向量机能够更准确地分类。

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《Future Technologies Conference》|2016年|749p|共5页
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作者
Parisa Naraei; Abdolreza Abhari; Alireza Sadeghian;
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中图分类 TP3-53;
关键词
Support vector machines; Diseases; Heart; Multilayer perceptrons; Data mining; Biological neural networks;

机译：支持向量机;疾病;心脏;多层的感觉;数据挖掘;生物神经网络;

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机译：多层感知器神经网络和支持向量机在医疗数据分类中的应用
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Application of multilayer perceptron neural networks and support vector machines in classification of healthcare data

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