THE NATURAL LANGUAGE PROCESSING METHOD APPLIED TO ANALYSIS OF "PROJECT SYPHILIS NO" INTERVENTIONS
Syphilis, Natural Language Processing, Epidemiology, Text Mining
Syphilis is a chronic infectious disease that remains a serious public health problem in much of the world. In Brazil, the rapid response to syphilis project, Syphilis No, was created in 2018. This project has several strategies to combat syphilis, including the creation of a group of supporters who worked in priority municipalities and produced thousands of text reports and added them to the platform. The objective of the work is to use the textual productions of the platform of the supporter of the Sífilis Não project, LUES, for text mining to understand the impact of syphilis in the territory. The texts will be analyzed using some Natural Language Processing (PLN) algorithms. In addition, the answers to the self-assessment questionnaires of supporters, supervisors and managers will be used, in order to find relationships between the productions carried out and their self-assessments. Associations of self-assessment modules with syphilis indicators and its impact of the epidemic in the territory will be tested. It is expected to understand the most effective strategies for reducing syphilis in the territories based on the support strategy and the LUES platform.