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首页> 外文会议>International Conference on Condition Monitoring Machinery Failure Prevention Technologies >Data fusion for identification of serious illness in children
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Data fusion for identification of serious illness in children

机译：数据融合，用于鉴定儿童严重疾病

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Children presenting to an emergency care provider, such as an out-of-hours GP or Emergency Department, frequently have minor, self-limiting infections. However, a few will have a serious infection or complication, requiring urgent investigation and treatment to reduce the risk of long-term disability or death. Vital signs can be measured quickly and non-invasively on these children. However, no single sign is sufficiently predictive to accurately identify the children at risk. This is because signs may be physiologically coupled (e.g. heart rate and temperature), and also because the normal range of some signs, such as the breathing rate and heart rate, change with the age of the child. We propose a data fusion technique to identify children with serious illness from a combination of non-invasive vital signs and the age of the child. The technique has been applied to a dataset collected in primary care situations, and has shown that sensitivities and specificities of over 70% can be achieved.
机译：提交给紧急护理提供者的儿童，例如室外GP或急诊部门，经常有轻微的自我限制的感染。然而，少数会有严重的感染或并发症，需要迫切调查和治疗，以降低长期残疾或死亡的风险。可以在这些儿童中快速和非侵入性测量生命的标志。但是，没有单一标志足以准确地预测，以准确识别风险的儿童。这是因为迹象可以生理耦合（例如心率和温度），并且还因为某些迹象的正常范围，例如呼吸率和心率，随着孩子的年龄而变化。我们提出了一种数据融合技术，从非​​侵入性生命体征和孩子的年龄识别严重疾病的儿童。该技术已应用于在初级护理情况下收集的数据集，并表明可以实现超过70％的敏感性和特异性。

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