Predicting the onset of overweight in Chinese high school students: a machine-learning approach in a one-year prospective cohort study.

Journal: Endocrine

PMID: 38856840

Abstract

OBJECTIVE: This study aimed to develop and evaluate machine-learning models for predicting the onset of overweight in adolescents aged 14‒17, utilizing easily collectible personal information.

Authors

Zikang Zhang

Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, PR China.
Wei Peng

Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States.
Shaoming Sun

Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, PR China. ssmjkcjzx@outlook.com.
Jianguo Ma

School of Electronics and Information Engineering, Tianjin University, Tianjin, China. Electronic address: majg@tju.edu.cn.
Yining Sun

Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.
Fangwen Zhang

Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, PR China.

Keywords

Adolescent China Cohort Studies East Asian People Female Humans Incidence Machine Learning Male Overweight Pediatric Obesity Prospective Studies Students

External Resources

View on PubMed Access via DOI PubMed (38856840)

Predicting the onset of overweight in Chinese high school students: a machine-learning approach in a one-year prospective cohort study.

Abstract

Authors

Keywords

External Resources

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