出版社：Grupo de Pesquisa Metodologias em Ensino e Aprendizagem em Ciências
摘要：Among the diseases that affect the male population, prostate cancer has increased the mortality rate among them, where it is the sixth malignant neoplasm in the world and in Brazil the first. Despite the initiatives to help the male population against prostate cancer, there is still a lack of guidance regarding diagnosis and treatment. However, the initiatives would be better targeted if they had the profiles of patients assisted by them, but it is still a field of research with gaps. In addition, data that can help are stored in large databases with a lot of information, mainly due to the computerization process of the health sector, which makes manual analysis of this data difficult. This work aims to determine the sociodemographic profile of Brazilians with prostate cancer through the Apriori algorithm with data from 2010 to 2019. With this, we applied the Apriori algorithm to the INCA database in order to have the rules of Association. In the end, it is clear that the factors of smoking, alcoholism, race and marital status are the factors that stood out the most as they appear in the rules with the highest levels of confidence. However, we infer that the brown race has a higher incidence of prostate cancer in Brazil. Despite the incompleteness of the optional data in the INCA database, the analysis carried out at the national level and the possibility of using it to guide campaigns in the context of men's health stands.
关键词：Prostate Cancer;Data Mining;Association Rules;Apriori Algorithm;Teaching in health.
