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Prediction of mortality in patients with cardiovascular disease using data mining methods

机译:使用数据采矿方法预测心血管疾病患者的死亡率

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Healthcare information systems store a huge amount of patient data, so the trend of the use of data mining in healthcare is on the rise. Heart and blood vessel diseases are a leading cause of mortality both worldwide and here in Bosnia and Herzegovina, and prevention, surveillance and treatment are of great public health importance. Based on data on patients with cardiovascular disease, collected from 2011 to 2017 at Mostar Hospital, models for mortality prediction using techniques for data tree mining, neural network and logistic regression are presented. The aim of this research is to compare the effectiveness of these methods in modeling the effectiveness of predicting mortality in patients with cardiovascular disease.
机译:医疗信息系统存储大量的患者数据,因此在医疗保健中使用数据挖掘的趋势正在上升。心脏病和血管疾病是世界各地的死亡原因,在波斯尼亚和黑塞哥维那,预防,监测和治疗具有很大的公共卫生意义。根据2011年至2017年在Mostar医院收集的关于心血管疾病患者的数据,提出了利用数据树挖掘,神经网络和逻辑回归的致命预测模型。该研究的目的是比较这些方法在模拟心血管疾病患者预测死亡率的有效性方面的有效性。

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