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Prediction of clinicians' treatment in preterm infants with suspected late-onset sepsis — An ML approach

机译:怀疑晚期脓毒症患者临床医生治疗的预测 - 一种方法 - 一种方法

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As a prevalent disease of preterm infants, late-onset neonatal sepsis has taken up a huge proportion of morbidity and mortality of newborn babies. We have been continuously capturing vital signs of preterm infants in NICU, and proposed a non-invasive method based on machine learning techniques to predict the clinicians' treatment on them. Then we provide evaluation of predictive models and prove their feasibility. Our models could help the pediatricians make wiser clinical decision, such as more accurate treatment, avoiding the abuse of antibiotics to some extent.
机译:作为早产儿的普遍存在婴儿,晚期新生儿败血症已经占据了巨大的发病率和新生儿的死亡率。我们一直在持续捕捉到尼古尔的早产儿的生命迹象,并提出了一种基于机器学习技术的非侵入性方法,以预测临床医生对它们的治疗。然后我们提供对预测模型的评估并证明他们的可行性。我们的车型可以帮助儿科医生制作更明智的临床决策,如更准确的治疗,避免在一定程度上滥用抗生素。

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