Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study: Comparação de algoritmos de aprendizagem de máquina para construir um modelo preditivo para detecção de diabetes não diagnosticada - ELSA-Brasil: estudo de acurácia

CONTEXT AND OBJECTIVE: Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study...

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Detalles Bibliográficos
Autores principales: Olivera, André Rodrigues, Roesler, Valter, Iochpe, Cirano, Schmidt, Maria Inês, Vigo, Álvaro, Barreto, Sandhi Maria, Duncan, Bruce Bartholow
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Associação Paulista de Medicina - APM 2017
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019841/
https://www.ncbi.nlm.nih.gov/pubmed/28746659
http://dx.doi.org/10.1590/1516-3180.2016.0309010217

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019841/
https://www.ncbi.nlm.nih.gov/pubmed/28746659
http://dx.doi.org/10.1590/1516-3180.2016.0309010217

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