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Real-time Multidimensional Temporal Analysis of Complex High Volume Physiological Data Streams in the Neonatal Intensive Care Unit

机译:新生重症监护室复杂高批量生产数据流的实时多维时间分析

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The intensive care of immature preterm infants is a challenging, dynamic clinical task that is complicated because these infants frequently develop a range of comorbidities as they grow and develop after their premature birth. Earliest reliable condition onset detection is a goal within this setting and high frequency physiological analysis is showing potential new pathophysiological indicators for earlier onset detection of several conditions. To realise this, a platform for multi-stream, multi-condition, multi-feature risk scoring is required. In this paper we demonstrate our multi-stream online analytics approach for condition onset detection and demonstrate a user interface approach for patient state that can be available in real-time to support condition risk scoring.
机译:未成熟的早产婴儿的重症监护是一个挑战性的,动态的临床任务是复杂的,因为这些婴儿经常发展一系列合并症,因为它们在早产之后发展和发展。最早可靠的条件开始检测是该设置内的目标,并且高频生理分析显示出潜在的新病理学指标,以提前发病检测若干条件。为了实现这一点,需要一个用于多流,多条件,多特征风险评分的平台。在本文中,我们展示了用于条件开始检测的多流在线分析方法,并展示可以实时提供的患者状态的用户界面方法,以支持条件风险评分。

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