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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...
Autores principales: | Mao, Yaqian, Zhu, Zheng, Pan, Shuyao, Lin, Wei, Liang, Jixing, Huang, Huibin, Li, Liantao, Wen, Junping, Chen, Gang |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
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 |
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