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Multivariate Adaptive Regression Spline in Ischemic and Hemorrhagic patient (case study)

机译:缺血性和出血性患者的多变量自适应回归条状(案例研究)

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In 2010, World Health Organization (WHO) predicted cardiovascular cases cause 73% death rate from total of heart function disorder in human. Stroke cause by disorganized blood circulation in human brain that increase of death in Estonia. Based on WHO data, Stroke suffered people that has age between 0 and 64 years old. The limitation of research is Ischemic and Hemorrhagic patients which are type of Stroke in a hospital, Tallinn, Estonia. The aim in the research is to classify modified risk factors of Ischemic and Hemorrhagic whom are alcohol consumption, smokers, physical activity habit, body mass index (BMI), and diet habit. Thus, it applied Multivariate Regression Spline (MARS). The method is non-parametric method to overcome missing value and to increase accuracy. As result, the classification modified risks factor of Ischemic and Hemorrhagic patient using MARS are alcohol consumption, diet habit, smokers, physical activity, and BMI. The MARS model is f(x) = 0,677 + 0,579 x alcohol consumption - 0,780 × diet habit + 0,383 x smoking habit - 0,409 x physical act - 0,045(bmi - 55, 87) + 0, 126(bmi -63.29) - 0,118(bmi - 66,4) + 0,077 (bmi - 74,47). The probability of Ischemic based on the variables is 0,442 and Hemorrhagic is 0,558 respectively. The accuracy of MARS method is 93,65% and misclassification 6,35% respectively.
机译:2010年,世界卫生组织(世卫组织)预测的心血管案件导致人类心脏功能障碍总量的73%死亡率。人脑中血液循环中的脑卒中引起的卒中原因增加了爱沙尼亚死亡的增加。基于谁数据,中风遭受了0至64岁之间的人。研究的限制是缺血性和出血性患者,其在医院,塔林,爱沙尼亚的脑卒中。研究的目的是对缺血性和出血性的缺血性和出血,吸烟者,身体活动习惯,体重指数(BMI)和饮食习惯进行分类的修改风险因素。因此,它应用了多变量回归样条(火星)。该方法是非参数方法来克服缺失值并提高精度。结果,使用火星的缺血性和出血患者的分类改良风险是醇消费,饮食习惯,吸烟者,身体活动和BMI。火星模型是f(x)= 0,677 + 0,579 x酒精消费 - 0,780×饮食习惯+ 0,383 x吸烟习惯 - 0,409 x物理法案 - 0,045(BMI - 55,87)+ 0,126(BMI -63.29) - 0,118 (BMI - 66,4)+ 0,077(BMI - 74,47)。基于变量的缺血性概率为0.442,出血分别为0.558。 MARS方法的准确性分别为93,65%,分别错误分类6,35%。

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