Image Pattern Recognition Combined With Data Mining for Diagnosis and Detection of Myocardial Infarction

被引：1
|
作者：
Tang, Xiaoqiang [1 ]
Zhang, Ming [1 ]
Shi, Haifeng [1 ]
Pan, Changjie [1 ]
机构：
[1] Nanjing Med Univ, Affiliated Changzhou Peoples Hosp 2, Dept Radiol, Changzhou 213164, Jiangsu, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
关键词：
Data mining; Diseases; Myocardium; Clustering algorithms; Databases; Ultrasonic variables measurement; Medical diagnostic imaging; myocardial infarction; association rules; pattern recognition;
D O I：
10.1109/ACCESS.2020.3014724
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
How to apply data analysis algorithms to China's primary hospitals is still a problem that needs to be solved. In order to effectively explore the pathogenesis of myocardial infarction disease, this study collected a large amount of real data as a basis for data analysis through data survey, improved traditional cluster analysis and data mining methods, and proposed effective data mining methods for myocardial infarction. In addition, this study analyzes data sources by implementing clustering analysis algorithms and combines data mining algorithms to provide decision support information for disease research. Finally, this study uses experimental methods of image data analysis combined with data mining methods to record the results. The research shows that the algorithm of this study has certain feasibility and can provide theoretical reference for subsequent related research.
引用
收藏
页码：146085 / 146092
页数：8
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