Labor contraction prediction via demographic and obstetrical information analysis

Zifang Huang, Mei Ling Shyu, James M. Tien, David J. Birnbach, Michael M. Vigoda

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

1 Scopus citations

Abstract

Designing an optimal dosing regimen for the systemic opioid remifentanil during labor necessitates the prediction of the pace of contractions, so that the drug can be given shortly before the pain of the contraction begins. The prediction and drug administration should be made early enough to allow for the administration of intravenous analgesia that will have maximal efficacy during contractions and little effect between contractions. Towards such a need, we propose a knowledge-assisted sequential pattern analysis framework to predict the changes in intrauterine pressure, which indicate the occurrence of labor contractions. In particular, a patient selection strategy is proposed to select a group of patients, from the stored record, who share similar demographic and obstetrical information with the current patient of interest. A sequential association rule mining approach is designed to learn the patterns of the contractions from the historical patient tracings, and to determine which demographic and obstetrical features have an impact on the contraction patterns. The promising experimental results show that the proposed framework is effective, robust, and efficient in predicting the labor contraction patterns.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012
Pages300-305
Number of pages6
DOIs
StatePublished - Dec 1 2012
Event2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012 - Philadelphia, PA, United States
Duration: Oct 4 2012Oct 7 2012

Publication series

NameProceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012

Other

Other2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012
CountryUnited States
CityPhiladelphia, PA
Period10/4/1210/7/12

Keywords

  • association rule mining
  • labor contraction prediction
  • pattern analysis
  • predictive models

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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