Predicting congenital syphilis cases: A performance evaluation of different machine learning models.
Igor Vitor TeixeiraMorgana Thalita da Silva LeiteFlávio Leandro de Morais MeloÉlisson da Silva RochaSara SadokAna Sofia Pessoa da Costa CarrarineMarília SantanaCristina Pinheiro RodriguesAna Maria de Lima OliveiraKeduly Vieira GadelhaCleber Matos de MoraisJudith KelnerPatricia Takako EndoPublished in: PloS one (2023)
The AdaBoost-BODS-Expert model, an Adaptive Boosting (AdaBoost) model that used attributes selected by health experts, presented the best results in terms of evaluation metrics and acceptance by health experts from PMCP. By using this model, the results are more reliable and allows adoption on a daily usage to classify possible outcomes of congenital syphilis using clinical and sociodemographic data.