Using CART for advanced prediction of asthma attacks based on telemonitoring data

Joseph Finkelstein, In Cheol Jeong

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

Abstract

Advanced prediction of asthma exacerbations may significantly improve patient quality of life and reduce costs of urgent care delivery. Majority of current algorithms predict who is likely to experience asthma exacerbation rather than when it is about to occur. We used data from asthma home-based telemonitoring for advanced prediction of asthma exacerbation. The goal of this project was to develop an algorithm that predicts asthma exacerbation one day in advance based on previous 7-day window. CART was used for predictive modeling. Resulting algorithm had specificity 0.971, sensitivity of 0.647, and accuracy of 0.809. We concluded that machine learning has great potential for advanced prediction of chronic disease exacerbations based on home telemonitoring data.

Original languageEnglish (US)
Title of host publication2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509014965
DOIs
StatePublished - Dec 7 2016
Externally publishedYes
Event7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016 - New York City, United States
Duration: Oct 20 2016Oct 22 2016

Other

Other7th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016
CountryUnited States
CityNew York City
Period10/20/1610/22/16

Keywords

  • artificial intelligence
  • asthma
  • Big data analytics
  • exacerbation prediction
  • telemonitoring

ASJC Scopus subject areas

  • Hardware and Architecture
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Finkelstein, J., & Jeong, I. C. (2016). Using CART for advanced prediction of asthma attacks based on telemonitoring data. In 2016 IEEE 7th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2016 [7777890] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UEMCON.2016.7777890