Development and validation of an explainable machine learning model for predicting osteoporosis in patients with type 2 diabetes mellitus

Development and validation of an explainable machine learning model for predicting osteoporosis in patients with type 2 diabetes mellitus

ObjectiveOsteoporosis is a common complication in patients with type 2 diabetes mellitus (T2DM), yet its screening rate remains low. This study aimed to develop and validate a cost-effective and interpretable machine learning (ML) model to predict the risk of osteoporosis in patients with T2DM.Metho...

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Bibliographic Details
Main Authors: Qipeng Wei, Zihao Liu, Xiaofeng Chen, Hao Li, Weijun Guo, Qingyan Huang, Jinxiang Zhan, Shiji Chen, Dongling Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Endocrinology
Subjects:
osteoporosis
type 2 diabetes mellitus
explainable machine learning
predictive model
risk assessment
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2025.1611499/full
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https://www.frontiersin.org/articles/10.3389/fendo.2025.1611499/full

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