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Data mining techniques to analyze the reason for home birth in Bangladesh

机译:数据挖掘技术分析孟加拉国家庭出生的原因

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Data Mining is the process of finding pattern or useful information from large volume of data. The goal of this paper is to find the reason behind the unusual high birth rate by applying data mining techniques, e.g., decision tree, neural network, Bayes Classifier, Ripper and Support Vector Machine. The datasets were collected from the baseline survey conducted by the maternal neonatal and child health programme by ICDDR, B. If we could find the reason(s), high birth rate at home could be avoided in future. Giving birth at home is very dangerous as many complications may arise during pregnancy as well during birth. From the opinions of experts and professionals, it could be said that the risk of mortality of new born during home birth is quite alarming and birth at hospital/clinics seemed to be the safest place to protect the health and well-being of the woman and her baby.
机译:数据挖掘是从大量数据中查找模式或有用信息的过程。本文的目的是通过应用数据挖掘技术(例如决策树,神经网络,贝叶斯分类器,开膛手和支持向量机)来找出导致异常高出生率的原因。这些数据集是从ICDDR B的孕产妇新生儿和儿童健康计划进行的基线调查中收集的。如果我们能找到原因,将来就可以避免在家中的高出生率。在家分娩是非常危险的,因为怀孕期间以及分娩过程中可能会出现许多并发症。从专家和专业人士的观点来看,可以说家庭生育期间新生儿的死亡风险令人震惊,医院/诊所的分娩似乎是保护妇女健康的最安全场所。她的孩子。

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