Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China

Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China

ObjectiveInsulin plays a central role in the regulation of energy and glucose homeostasis, and insulin resistance (IR) is widely considered as the “common soil” of a cluster of cardiometabolic disorders. Assessment of insulin sensitivity is very important in preventing and treating IR-related diseas...

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Bibliographic Details
Main Authors: Hao Zhang, Tianshu Zeng, Jiaoyue Zhang, Juan Zheng, Jie Min, Miaomiao Peng, Geng Liu, Xueyu Zhong, Ying Wang, Kangli Qiu, Shenghua Tian, Xiaohuan Liu, Hantao Huang, Marina Surmach, Ping Wang, Xiang Hu, Lulu Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Endocrinology
Subjects:
insulin sensitivity assessment
machine learning
community settings
primary care settings
risk factors
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2024.1292346/full

Internet

https://www.frontiersin.org/articles/10.3389/fendo.2024.1292346/full

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