Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm

Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm

ObjectiveThe aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.MethodsThis study was a retrospective cohort study. The s...

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Bibliographic Details
Main Authors: Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-09-01
Series:Frontiers in Endocrinology
Subjects:
impaired fasting glucose
prediction model
artificial intelligence
cohort study
middle-aged and elderly people
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2024.1368225/full
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https://www.frontiersin.org/articles/10.3389/fendo.2024.1368225/full

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