{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T20:34:55Z","timestamp":1761165295249,"version":"build-2065373602"},"reference-count":13,"publisher":"Sociedade Brasileira de Computa\u00e7\u00e3o - SBC","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"Investigamos a efetividade de m\u00e9todos supervisionados de aprendizado de m\u00e1quina na identifica\u00e7\u00e3o de indiv\u00edduos possivelmente n\u00e3o diagnosticados ou com alto risco de desenvolver Diabetes Mellitus (DM) no contexto de operadoras de sa\u00fade suplementar. O cen\u00e1rio \u00e9 desafiador: h\u00e1 apenas dados administrativos indiretos (tipo e frequ\u00eancia de exames), sem resultados cl\u00ednicos, al\u00e9m de baixa separabilidade entre classes e incerteza nos r\u00f3tulos. Avaliamos tr\u00eas classificadores (XGBoost, Random Forest e Regress\u00e3o Log\u00edstica), obtendo desempenho robusto (Macro-F1 de 90,1%). A an\u00e1lise de erros sugere que falsos positivos podem indicar casos ainda n\u00e3o diagnosticados, enquanto falsos negativos podem refletir controle cl\u00ednico inadequado.<\/jats:p>","DOI":"10.5753\/sbbd.2025.247707","type":"proceedings-article","created":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T19:26:36Z","timestamp":1761074796000},"page":"788-794","source":"Crossref","is-referenced-by-count":0,"title":["Quando os Erros Informam: Apoio ao Diagn\u00f3stico de Diabetes em Cen\u00e1rios de Alta Incerteza"],"prefix":"10.5753","author":[{"given":"Samuel Norberto","family":"Alves","sequence":"first","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Celso","family":"Fran\u00e7a","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Regina T. 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Improving healthcare prediction of diabetic patients using knn imputed features and tri-ensemble model. IEEE Access, 12:16783\u201316793.","DOI":"10.1109\/ACCESS.2024.3359760"},{"key":"2","unstructured":"ANS (2021). Promo\u00e7\u00e3o da sa\u00fade e preven\u00e7\u00e3o de doen\u00e7as - PROMOPREV - [link]<\/a>. Atualizado em 06\/06\/2025."},{"key":"3","doi-asserted-by":"crossref","unstructured":"Banday, M. Z., Sameer, A. S., and Nissar, S. (2020). Pathophysiology of diabetes: An overview. Avicenna journal of medicine, 10(04):174\u2013188.","DOI":"10.4103\/ajm.ajm_53_20"},{"key":"4","doi-asserted-by":"crossref","unstructured":"Cunha, W. et al. (2023). An effective, efficient, and scalable confidence-based instance selection framework for transformer-based text classification. 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