Prediction of Stroke using Data Mining Classification Techniques

被引：3
|
作者：
Almadani, Ohoud [1 ]
Alshammari, Riyad [2 ]
机构：
[1] King Abdul Aziz Med City, Pharmacut Care Dept, Riyadh, Saudi Arabia
[2] King Saud bin Abdulaziz Univ Hlth Sci, KAIMRC, Minstry Natl Guard Hlth Affairs, Riyadh, Saudi Arabia
来源：
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2018年 / 9卷 / 01期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Stroke; data mining; classification;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Stroke is a neurological disease that occurs when a brain cells die as a result of oxygen and nutrient deficiency. Stroke detection within the first few hours improves the chances to prevent complications and improve health care and management of patients. In addition, significant effect of medications that were used as treatment for stroke would appear only if they were given within the first three hours since the beginning of stroke. A framework has been designed based on data mining techniques on Stroke data set that is obtained from Ministry of National Guards Health Affairs hospitals, Kingdom of Saudi Arabia. A data mining model was built with 95% accuracy. Furthermore, this study showed that patient with the following medical conditions, such as heart diseases (hypertension mainly), immunity diseases, diabetes militias, kidney diseases, hyperlipidemia, epilepsy, or blood (platelets) disorders has a higher probability to develop stroke.
引用
收藏
页码：457 / 460
页数：4
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