Combination of Machine Learning Techniques to Predict Overweight/Obesity in Adults.

ABSTRACT: (1) Background: Artificial intelligence using machine learning techniques may help us to predict and prevent obesity. The aim was to design an interpretable prediction algorithm for overweight/obesity risk based on a combination of different machine learning techniques. (2) Methods: 38 variables related to sociodemographic, lifestyle, and health aspects from 1179 residents in Madrid were collected and used to train predictive models. Accuracy, precision, and recall metrics were tested and compared between nine classical machine learning techniques and the predictive model based on a combination of those classical machine learning techniques. Statistical validation was performed. The shapely additive explanation technique was used to identify the variables with the greatest impact on weight

SUBMITTER: Gutierrez-Gallego A 

PROVIDER: S-EPMC11355742 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature