A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults

A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults

Abstract Background Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk factors and predict disease probability. Howe...

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Bibliographic Details
Main Authors: Yuyi Peng, Chi Zhang, Bo Zhou
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Geriatrics
Subjects:
Copy number variants
Osteoporosis
Prediction model
Machine learning
Low sodium salt intake
Online Access:https://doi.org/10.1186/s12877-025-05840-w
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https://doi.org/10.1186/s12877-025-05840-w

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