Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project

Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting in...

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Detalles Bibliográficos
Autores principales: Alghamdi, Manal, Al-Mallah, Mouaz, Keteyian, Steven, Brawner, Clinton, Ehrman, Jonathan, Sakr, Sherif
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5524285/
https://www.ncbi.nlm.nih.gov/pubmed/28738059
http://dx.doi.org/10.1371/journal.pone.0179805

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5524285/
https://www.ncbi.nlm.nih.gov/pubmed/28738059
http://dx.doi.org/10.1371/journal.pone.0179805

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