Visualization obesity risk prediction system based on machine learning

Obesity is closely associated with various chronic diseases.Therefore, accurate, reliable and cost-effective methods for preventing its occurrence and progression are required. In this study, we developed a visualized obesity risk prediction system based on machine learning techniques, aiming to ach...

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Bibliographic Details
Published in:Scientific reports 2024-09, Vol.14 (1), p.22424-9, Article 22424
Main Authors: Du, Jinsong, Yang, Sijia, Zeng, Yijun, Ye, Chunhong, Chang, Xiao, Wu, Shan
Format: Article
Language:English
Subjects:
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Adult
Biochemical tests
Body composition
Body Mass Index
Female
Humanities and Social Sciences
Humans
Learning algorithms
Machine Learning
Male
Middle Aged
multidisciplinary
Obesity
Obesity - epidemiology
Predictions
Risk Assessment - methods
Risk Factors
Science
Science (multidisciplinary)
Weight control
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Summary:Obesity is closely associated with various chronic diseases.Therefore, accurate, reliable and cost-effective methods for preventing its occurrence and progression are required. In this study, we developed a visualized obesity risk prediction system based on machine learning techniques, aiming to achieve personalized comprehensive health management for obesity. The system utilized a dataset consisting of 1678 anonymized health examination records, including individual lifestyle factors, body composition, blood routine, and biochemical tests. Ten multi-classification machine learning models, including Random Forest and XGBoost, were constructed to identify non-obese individuals (BMI 
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-73826-6