Assessing of the Importance of Medical Parameters on the Risk of the Myocardial Infraction Using Statistical Analysis and Neural Networks

被引：0

作者：

Peterkova, Andrea ^{[1
]}

Michalconok, German ^{[1
]}

机构：

[1] Slovak Univ Technol Bratislava, Inst Appl Informat Automat & Mechatron, Fac Mat Sci & Technol Trnava, Bratislava, Slovakia

来源：

SOFTWARE ENGINEERING TRENDS AND TECHNIQUES IN INTELLIGENT SYSTEMS, CSOC2017, VOL 3 | 2017年 / 575卷

关键词：

Statistical analysis; Data mining; Clinical data; Ischemic heart disease;

D O I：

10.1007/978-3-319-57141-6_25

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this article is to assess or to complete the medical hypothesis on the further prepared clinical data with the use of data mining methods. In our research, we focus on cardiological datasets of patients who underwent coronary angiography and who were indicated for the ischemic heart disease. These patients are divided into four stages of clinical diagnosis. The clinical hypothesis is pointing on the clinical parameters, which have significant impact on the probability of the occurrence of the myocardial infraction. For the data analysis, we use STATISTICA 13 software.

引用

页码：237 / 243

页数：7