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首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Application of Decision Tree in the Prediction of Periventricular Leukomalacia (PVL) Occurrence in Neonates After Heart Surgery
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Application of Decision Tree in the Prediction of Periventricular Leukomalacia (PVL) Occurrence in Neonates After Heart Surgery

机译：决策树在心脏手术后脑病患者中脑室白血病（PVL）发生预测中的应用

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This paper is concerned with the prediction of the occurrence of periventricular leukomalacia (PVL) that occurs in neonates after heart surgery. The data which is collected over a period of 12 hours after cardiac surgery contains vital measurements as well as blood gas measurements with different resolutions. Vital data measured using near-inferred spectroscopy (NIRS) at the sampling rate of 0.25 Hz and blood gas measurement up to 12 times with irregular time intervals for 35 patients collected at Children's Hospital of Philadelphia(CHOP) are used for this study. Features derived from the data include statistical moments (mean, variance, skewness and kurtosis), trend and minimum and maximum values of the vital data and rate of change, time weighted mean and a custom defined out of range index (ORI) for the blood gas data. A decision tree is developed for the vital data in order to identify the most important vital measurements. In addition, a decision tree is developed for blood gas data to find important factors for the prediction of PVL occurrence. Results show that in the blood gas data, maximum rate of change of concentration of bicarbonate ions in blood (HCO_3) and minimum rate of change of partial pressure of dissolved CO_2 in the blood (PaCO_2) are the two most important factors for prediction of the PVL. Also important are the kurtosis of heart rate and hemoglobin values.
机译：本文关注与心脏手术后发生新生儿脑室周围白质软化症（PVL）发生的预测。这是收集心脏手术之后的12小时内的数据包含重要的测量，以及具有不同分辨率的血液气体测量。利用在0.25赫兹和血液气体测量向上的采样率的12倍与在费城儿童医院（CHOP）收集35例不规则的时间间隔近推断光谱（NIRS）测量的生命数据被用于该研究。从数据导出的特征包括统计矩（平均值，方差，偏度和峰度），趋势，最小值以及生物体数据和变化率的最大值，时间加权平均值和一个自定义的范围指数（ORI）的出用于血液气体数据。决策树，以确定最重要的生命三围为重要的数据开发的。此外，决策树血气数据开发找到PVL发生的预测的重要因素。结果表明，在血液中的气体的数据，在血液（HCO_3）碳酸氢根离子的浓度的变化，并溶解CO_2的分压的变化的最小速率在血液（PaCO_2）的最大速率是用于预测的两个最重要的因素PVL。同样重要的是心脏率和血红蛋白值的峰度。

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