Vianna Rossana Cristina Xavier Ferreira, Moro Claudia Maria Cabral de Barra, Moysés Samuel Jorge, Carvalho Deborah, Nievola Julio Cesar
Secretaria do Estado da Saúde do Paraná, Curitiba, Brasil.
Cad Saude Publica. 2010 Mar;26(3):535-42. doi: 10.1590/s0102-311x2010000300011.
This study aims to identify patterns in maternal and fetal characteristics in the prediction of infant mortality by incorporating innovative techniques like data mining, with proven relevance for public health. A database was developed with infant deaths from 2000 to 2004 analyzed by the Committees for the Prevention of Infant Mortality, based on integration of the Information System on Live Births (SINASC), Mortality Information System, and Investigation of Infant Mortality in the State of Paraná. The data mining software was WEKA (open source). The data mining conducts a database search and provides rules to be analyzed to transform the data into useful information. After mining, 4,230 rules were selected: teenage pregnancy plus birth weight < 2,500 g, or post-term birth plus teenage mother with a previous child or intercurrent conditions increase the risk of neonatal death. The results highlight the need for greater attention to teenage mothers, newborns with birth weight < 2,500 g, post-term neonates, and infants of mothers with intercurrent conditions, thus corroborating other studies.
本研究旨在通过纳入数据挖掘等创新技术，识别预测婴儿死亡率的母婴特征模式，这些技术已被证明与公共卫生相关。基于巴拉那州活产信息系统（SINASC）、死亡率信息系统和婴儿死亡率调查的整合，开发了一个包含2000年至2004年婴儿死亡情况的数据库，由预防婴儿死亡委员会进行分析。数据挖掘软件为WEKA（开源）。数据挖掘对数据库进行搜索并提供待分析的规则，以将数据转化为有用信息。挖掘后，选择了4230条规则：青少年怀孕加上出生体重<2500克，或过期产加上有前一个孩子的青少年母亲或并发疾病会增加新生儿死亡风险。结果强调需要更加关注青少年母亲、出生体重<2500克的新生儿、过期产新生儿以及患有并发疾病母亲的婴儿，从而证实了其他研究。
