High Frequency Data Stream Event Correlation for Complex Neonatal Medical Alerts

近20%的新生儿在出生后需要重症监护。几种电子仪器监测婴儿的生命体征，如血氧、血压和心率。新生儿临床管理中的一个主要限制是，这些监测仪产生的数据没有整合在一起，以实现对病情恶化的警报或对可能的病情开始的早期预警。该项目将开发一种方法和技术，通过在事件流处理器中使用代理来支持复杂新生儿医疗警报的新生儿临床和生理数据的交叉关联，从而提高存活率。

Nearly twenty percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the data generated by these monitors is not integrated to enable the alerting of condition deterioration or early warning of possible condition onset. This project will develop a methodology and technology that supports the cross correlation of neonatal clinical and physiological data for complex neonatal medical alerts, through the use of agents within an event stream processor, resulting in higher survival rates.