B4459 - A Machine Learning Approach for Predicting Childrens Future BMI - 15/01/2024

B number: 
Principal applicant name: 
Kang Lee | University of Toronto (Canada)
Yuan Hong Sun
Title of project: 
A Machine Learning Approach for Predicting Children’s Future BMI
Proposal summary: 

Child development involves not only mental but also physical development. Children’s future height, weight, and in particular, body mass index (BMI), is a major concern for parents and physicians due to the current pediatric obesity epidemic. Currently, these predicted measurements are calculated through clinical procedures. To make this process more convenient for parents, we are developing a machine-learning approach for predicting children’s future height, weight, and BMI for a certain number of years and implementing it digitally as an online assessment tool. We plan to use a longitudinal dataset of children’s physical examination data.

Impact of research: 
We believe this study and the subsequent online tool can greatly help parents, guardians, and schools monitor the general physical health of children and take the initiative in building healthier lifestyles for children.
Date proposal received: 
Sunday, 3 December, 2023
Date proposal approved: 
Monday, 18 December, 2023
Statistics/methodology, Obesity, Computer simulations/modelling/algorithms, Statistical methods, BMI