Machine Learning For Tuning, Selection, And Ensemble Of Multiple Risk Scores For Predicting Type 2 Diabetes

BACKGROUND: This study proposes the use of machine learning algorithms to improve the accuracy of type 2 diabetes predictions using non-invasive risk score systems. METHODS: We evaluated and compared the prediction accuracies of existing non-invasive risk score systems using the data from the REACTI...

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Detalles Bibliográficos
Autores principales: Liu, Yujia, Ye, Shangyuan, Xiao, Xianchao, Sun, Chenglin, Wang, Gang, Wang, Guixia, Zhang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842709/
https://www.ncbi.nlm.nih.gov/pubmed/31807099
http://dx.doi.org/10.2147/RMHP.S225762

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842709/
https://www.ncbi.nlm.nih.gov/pubmed/31807099
http://dx.doi.org/10.2147/RMHP.S225762

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