Factors that contribute towards children´s mortality assessed through data mining

• Autor(a) principal: Sartorelli, Ana Paula
• Data de Publicação: 2017
• Outros Autores: Gomes, Denilsen Carvalho, Cubas, Marcia Regina, Carvalho, Deborah Ribeiro
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Saúde e Pesquisa (Online)
• Texto Completo: https://periodicos.unicesumar.edu.br/index.php/saudpesq/article/view/5879
• topic: Infant Mortality; Data mining; Artificial intelligence; Mortalidade infantil; Mineração de dados; Inteligência artificial; Politicas publicas

To complement factors related to child mortality. Data were retrieved from the Information System on Live Births and from the Information System of Mortality, between 2010 and 2014 in a municipality in the state of Paraná, Brazil. Descriptive statistics were taken and data mining was employed through algorithms J48 and NPP. Relationships between low weight at birth and pregnancy age were identified; it has been reported that mothers with more than one infant death had premature children; 56.8% of deaths were avoidable and lacked adequate care during pregnancy. Low weight at birth, pregnancy age and anomalies are factors related to child mortality. Public policies towards mothers´ health and towards premature births are required.