Application of Machine Learning Techniques to Predict Teenage Obesity Using Earlier Childhood Measurements from Millennium Cohort Study-Reference-Cited by-同舟云学术

Application of Machine Learning Techniques to Predict Teenage Obesity Using Earlier Childhood Measurements from Millennium Cohort Study

Published:2023-08-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 7th International Conference on Cloud and Big Data Computing
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Author:

Singh Balbir¹^ORCID,Gorbenko Anatoliy¹^ORCID,Palczewska Anna¹^ORCID,Tawfik Hissam²^ORCID

Affiliation:

1. School of Built Environment, Engineering and Computing, Leeds Beckett University, United Kingdom

2. Department of Electrical Engineering, University of Sharjah, United Arab Emirates

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3616131.3616139

Reference31 articles.

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2. Age-specific stabilization in obesity prevalence in German children: A cross-sectional study from 1999 to 2008

3. Butland , B. 2007 . Tackling Obesities: Future Choices – Project report 2 nd Edition. Butland, B. 2007. Tackling Obesities: Future Choices – Project report 2nd Edition.

4. SMOTE: Synthetic Minority Over-sampling Technique

5. Cole , T.J. 2000 . Establishing a standard definition for child overweight and obesity worldwide . BMJ 2000:320:1-6. (2000). Cole, T.J. 2000. Establishing a standard definition for child overweight and obesity worldwide. BMJ 2000:320:1-6. (2000).