A Survey on Machine and Deep Learning Models for Childhood and Adolescent Obesity

Author:

Siddiqui HeraORCID,Rattani AjitaORCID,Woods Nikki K.,Cure Laila,Lewis Rhonda K.,Twomey Janet,Smith-Campbell Betty,Hill Twyla J.

Funder

President’s Convergence Science Initiative Grant from Wichita State University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Reliable prediction of childhood obesity using only routinely collected EHRs is possible;2024-01-30

2. Classification of Obesity among South African Female Adolescents: Comparative Analysis of Logistic Regression and Random Forest Algorithms;International Journal of Environmental Research and Public Health;2023-12-19

3. Obesity Risk Prediction Using Machine Learning Approach;2023 International Conference on Networking and Communications (ICNWC);2023-04-05

4. Probable Deviation Outlier-Based Classification of Obesity with Eating Habits and Physical Condition;Intelligent Manufacturing and Energy Sustainability;2023

5. Performance Analysis of Supervised Machine Learning Algorithm for Prediction of Diabetes;2022 International Conference on Edge Computing and Applications (ICECAA);2022-10-13

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