A comprehensive analysis of triggers and risk factors for asthma based on machine learning and large heterogeneous data sources

Wenli Zhang, Sudha Ram

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Asthma is a common chronic health condition affecting millions of people in the United States. While asthma cannot be cured, it can be managed if we identify and understand triggers and risk factors that cause asthma exacerbations. However, this is challenging because these triggers and risk factors are complex and interconnected, and there are limitations to current mainstream approaches for identifying them. The recent availability of massive amounts of heterogeneous data has opened up new possibilities for asthma triggers and risk factors analyses. In this study, we introduce a data-driven framework, adapt and integrate multiple advanced machine learning techniques, and perform an empirical analysis to (1) derive characteristics of self-reported asthma patients from social media, (2) enable integration and repurposing of highly heterogeneous and commonly available datasets, and (3) uncover the sequential patterns of asthma triggers and risk factors, and their relative importance, both of which are difficult to achieve via retrospective cohort-based studies. Our methods and results can provide guidance for developing asthma management plans and interventions for specific subpopulations and, eventually, have the potential to reduce the societal burden of asthma.

Original languageEnglish (US)
Pages (from-to)305-349
Number of pages45
JournalMIS Quarterly: Management Information Systems
Volume44
Issue number1
DOIs
StatePublished - Mar 2020

Keywords

  • Asthma triggers/risk factors
  • Chronic disease management
  • Convolutional neural networks
  • Design science
  • Distant supervision
  • Geometric inference
  • Machine learning
  • Random forest
  • Sequential pattern mining

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Science Applications
  • Information Systems and Management

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