Machine Learning-Based Asthma Attack Prediction Models From Routinely Collected Electronic Health Records: Systematic Scoping Review.

Journal: JMIR AI
Published Date: Dec 7, 2023

Abstract

BACKGROUND: An early warning tool to predict attacks could enhance asthma management and reduce the likelihood of serious consequences. Electronic health records (EHRs) providing access to historical data about patients with asthma coupled with machine learning (ML) provide an opportunity to develop such a tool. Several studies have developed ML-based tools to predict asthma attacks.

Authors

  • Arif Budiarto
    Asthma UK Center for Applied Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.
  • Kevin C H Tsang
    Asthma UK Center for Applied Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.
  • Andrew M Wilson
    Norwich Medical School, University of East Anglia, Norwich, United Kingdom.
  • Aziz Sheikh
    Asthma UK Center for Applied Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.
  • Syed Ahmar Shah
    Asthma UK Center for Applied Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.

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