Visualization obesity risk prediction system based on machine learning.

ABSTRACT: 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 < 25), class 1 obese individuals (25 ≤ BMI < 30), and class 2 obese individuals (30 ≤ BMI). By evaluating the

SUBMITTER: Du J 

PROVIDER: S-EPMC11439005 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature