AUTHOR=da Rocha Marcella A. , dos Santos Marquiony M. , Fontes Raphael S. , de Melo Andréa S. P. , Cunha-Oliveira Aliete , Miranda Angélica E. , de Oliveira Carlos A. P. , Oliveira Hugo Gonçalo , Gusmão Cristine M. G. , Lima Thaísa G. F. M. S. , Pinto Rafael , Barros Daniele M. S. , Valentim Ricardo A. de M. TITLE=The Text Mining Technique Applied to the Analysis of Health Interventions to Combat Congenital Syphilis in Brazil: The Case of the “Syphilis No!” Project JOURNAL=Frontiers in Public Health VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.855680 DOI=10.3389/fpubh.2022.855680 ISSN=2296-2565 ABSTRACT=
Congenital syphilis (CS) remains a threat to public health worldwide, especially in developing countries. To mitigate the impacts of the CS epidemic, the Brazilian government has developed a national intervention project called “Syphilis No.” Thus, among its range of actions is the production of thousands of writings featuring the experiences of research and intervention supporters (RIS) of the project, called field researchers. In addition, this large volume of base data was subjected to analysis through data mining, which may contribute to better strategies for combating syphilis. Natural language processing is a form of knowledge extraction. First, the database extracted from the “LUES Platform” with 4,874 documents between 2018 and 2020 was employed. This was followed by text preprocessing, selecting texts referring to the field researchers' reports for analysis. Finally, for analyzing the documents, N-grams extraction (