Identifying growth-patterns in children by applying cluster analysis to electronic medical records

Moumita Bhattacharya, Deborah Ehrenthal, Hagit Shatkay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Obesity is one of the leading health concerns in the United States. Researchers and health care providers are interested in understanding factors affecting obesity and detecting the likelihood of obesity as early as possible. In this paper, we set out to recognize children who have higher risk of obesity by identifying distinct growth patterns in them. This is done by using clustering methods, which group together children who share similar body measurements over a period of time. The measurements characterizing children within the same cluster are plotted as a function of age. We refer to these plots as growth-pattern curves. We show that distinct growth-pattern curves are associated with different clusters and thus can be used to separate children into the topmost (heaviest), middle, or bottom-most cluster based on early growth measurements.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
EditorsHuiru Zheng, Xiaohua Tony Hu, Daniel Berrar, Yadong Wang, Werner Dubitzky, Jin-Kao Hao, Kwang-Hyun Cho, David Gilbert
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages348-351
Number of pages4
ISBN (Electronic)9781479956692
DOIs
StatePublished - Dec 29 2014
Event2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 - Belfast, United Kingdom
Duration: Nov 2 2014Nov 5 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014

Other

Other2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
Country/TerritoryUnited Kingdom
CityBelfast
Period11/2/1411/5/14

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics

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