A new data mining methodology applied to the modelling of the influence of diet and lifestyle on the value of bone mineral density in post-menopausal women

DOI10.1080/00207160902783557zbMath1176.62113OpenAlexW1982298138MaRDI QIDQ3643173

No author found.

Publication date: 10 November 2009

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160902783557

zbMATH Keywords

data miningbody mass index (BMI)multivariate adaptive regression splines (MARS)principal components analysis (PCA)food frequency questionnairebone mineral density (BMD)diet history questionnairequantitative computed tomographyrisk factor monitoring and methods branch

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)

Related Items (3)

A comparison of several machine learning techniques for the centerline segregation prediction in continuous cast steel slabs and evaluation of its performance ⋮ Forecast of the higher heating value in biomass torrefaction by means of machine learning techniques ⋮ Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions

Cites Work

• Multivariate adaptive regression splines

This page was built for publication: A new data mining methodology applied to the modelling of the influence of diet and lifestyle on the value of bone mineral density in post-menopausal women