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Predicting preterm birth in maternity care by means of data mining

机译:通过数据挖掘预测产妇保健中的早产

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摘要

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after thebirth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm birthsin a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assistingphysicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.
机译:在世界范围内,大约9%的孩子出生时的劳动时间少于37周,这给早产儿带来了风险,早产儿不准备在出生后不久就开始发展许多基本功能。为了确保产科医生及时监控那些危险的妊娠以避免这些问题,在本研究中引入了数据挖掘(DM)模型,使用来自3376名入院患者(女性)的数据来预测真实环境中的早产。波尔图中心医院的孕产妇和围产保健部门。开发了一种预测早产的灵敏指标,以帮助医师进行有关患者观察的决策过程。可能获得有希望的结果,灵敏度和特异性值分别达到96%和98%。

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