Identifying Symptom Clusters in Women Experiencing Preterm Birth

Ting He, Casey Overby

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

Abstract

Preterm birth affected about 10% infants born in the U.S. in 2016. This project was a secondary analysis of data drawn from a preterm birth prediction study to assess whether psychological symptom clusters exist among pregnant women. A symptom cluster exists when two or more symptoms co-occur, are related to each other, and are stable. We found one psychological symptom pair that satisfied these conditions: anxiety & self-esteem. This finding has potential to help guide symptom assessment among pregnant women.

Original languageEnglish (US)
Title of host publicationACM-BCB 2018 - Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
PublisherAssociation for Computing Machinery, Inc
Number of pages1
ISBN (Electronic)9781450357944
DOIs
StatePublished - Aug 15 2018
Event9th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2018 - Washington, United States
Duration: Aug 29 2018Sep 1 2018

Other

Other9th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2018
CountryUnited States
CityWashington
Period8/29/189/1/18

Keywords

  • Correlation
  • Preterm birth
  • Symptom clusters

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Health Informatics
  • Biomedical Engineering

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