Value of machine learning algorithms for predicting diabetes risk: A subset analysis from a real‐world retrospective cohort study

AIMS/INTRODUCTION: To compare the application value of different machine learning (ML) algorithms for diabetes risk prediction. MATERIALS AND METHODS: This is a 3‐year retrospective cohort study with a total of 3,687 participants being included in the data analysis. Modeling variable screening and p...

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Detalles Bibliográficos
Autores principales: Mao, Yaqian, Zhu, Zheng, Pan, Shuyao, Lin, Wei, Liang, Jixing, Huang, Huibin, Li, Liantao, Wen, Junping, Chen, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889616/
https://www.ncbi.nlm.nih.gov/pubmed/36345236
http://dx.doi.org/10.1111/jdi.13937

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889616/
https://www.ncbi.nlm.nih.gov/pubmed/36345236
http://dx.doi.org/10.1111/jdi.13937

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