<abstract><p>About 6.5 million people are infected with Chagas disease (CD) globally, and WHO estimates that $ &gt; million people worldwide suffer from ChHD. Sudden cardiac death (SCD) represents one of the leading causes of death worldwide and affects approximately 65% of ChHD patients at a rate of 24 per 1000 patient-years, much greater than the SCD rate in the general population. Its occurrence in the specific context of ChHD needs to be better exploited. This paper provides the first evidence supporting the use of machine learning (ML) methods within non-invasive tests: patients' clinical data and cardiac restitution metrics (CRM) features extracted from ECG-Holter recordings as an adjunct in the SCD risk assessment in ChHD. The feature selection (FS) flows evaluated 5 different groups of attributes formed from patients' clinical and physiological data to identify relevant attributes among 57 features reported by 315 patients at HUCFF-UFRJ. The FS flow with FS techniques (variance, ANOVA, and recursive feature elimination) and Naive Bayes (NB) model achieved the best classification performance with 90.63% recall (sensitivity) and 80.55% AUC. The initial feature set is reduced to a subset of 13 features (4 Classification; 1 Treatment; 1 CRM; and 7 Heart Tests). The proposed method represents an intelligent diagnostic support system that predicts the high risk of SCD in ChHD patients and highlights the clinical and CRM data that most strongly impact the final outcome.</p></abstract>

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Este artigo apresenta o desenvolvimento de um jogo para dispositivos móveis que transmite conceitos de educação financeira para alunos de escolas rurais. Sua criação foi norteada pelos princípios de gamificação e user experience (UX). O jogo possui níveis com perguntas sobre situações do cotidiano do sertão nordestino e um sistema de recompensa através de moedas que podem ser usadas na loja do jogo ou guardadas. O aplicativo foi testado com 15 alunos, obtendo um alto grau de aceitação e jogabilidade. Em estudos externos, o software foi analisado, avaliado e enquadrado como objeto de aprendizagem. Atualmente, pode ser baixado na play store da Google.