Resumo
Introdução: os métodos de aprendizagem automática permitem o manuseamento de dados estruturados e não estruturados para construir modelos preditivos e apoiar a tomada de decisões. Objetivo: identificar os métodos de aprendizagem automática aplicados para prever o comportamento epidemiológico das arboviroses utilizando dados de vigilância epidemiológica. Metodologia: foi realizada pesquisa na EMBASE e PubMed, análise bibliométrica e síntese da informação. Resultados: foram selecionados 41 documentos, todos publicados na última década. A palavra-chave mais frequente foi dengue. A maioria dos autores (88.3 %) participou num artigo de investigação. Foram encontrados 16 métodos de aprendizagem de máquinas, sendo o mais frequente o Sistema Artificial de Rede Neural seguido de Máquinas de Vetores de Suporte. Conclusões: na última década, aumentou a publicação de trabalhos que pretendem prever o comportamento epidemiológico de arbovirose por meio de diversos métodos de aprendizagem automática que incorporam séries de tempo dos casos, variáveis climatológicas, e outras fontes de informação de dados abertos.
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