ECG Meta分析中的数据采掘技术综述
A Survey on Various Data Mining Techniques for ECG Meta Analysis
摘要：
数据采掘是从不同的角度对信息进行检验，并将其压缩为相关数据的过程。这些数据也可以用来增加收入。数据采掘也被称为数据或知识发现。数据采掘的基本目的是寻找具有最小用户输入和努力的模式。数据采掘在各个领域都起着非常关键的作用。有各种各样的数据采掘程序可以连接在不同的创新领域。通过使用数据采掘技术，观察到花费更少的时间来更准确地预测任何疾病。在本文中，我们将审查各种数据采掘技术分类，回归和聚类，并将这些算法应用于心电图数据集。这项工作的目的是确定最合适的数据采掘技术，并使用它来提高分析心电图数据的准确性，以更好的决策。
英文摘要：
Data Mining is the process of examining the information from different point of view and compressing it for the relevant data. This data can also be utilized to build the incomes. Data Mining is also known as Data or Knowledge Discovery. The basic purpose of data mining is to search patterns which have minimal user inputs and efforts. Data Mining plays a very crucial role in the various fields. There are various data mining procedures which can be connected in different fields of innovation. By using data mining techniques, it is observed that less time is taken for the prediction of any disease with more accuracy. In this paper we would review various data mining techniques which are categorized under classification, regression and clustering and apply these algorithms over an ECG dataset. The purpose of this work is to determine the most suitable data mining technique and use it to improve the accuracy of analyzing ECG data for better decision making.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
