This paper is in the following e-collection/theme issue:

Reviews in AI (13) Applications of AI (130)

Published on in Vol 2 (2023)

This is a member publication of The University of Edinburgh, Usher Institute, Edinburgh, United Kingdom

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46717, first published .
Machine Learning–Based Asthma Attack Prediction Models From Routinely Collected Electronic Health Records: Systematic Scoping Review

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

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

Authors of this article:

Arif Budiarto1, 2 Author Orcid Image ;   Kevin C H Tsang1 Author Orcid Image ;   Andrew M Wilson3, 4 Author Orcid Image ;   Aziz Sheikh1 Author Orcid Image ;   Syed Ahmar Shah1 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

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  2. Lisik D, Basna R, Dinh T, Hennig C, Shah S, Wennergren G, Goksör E, Nwaru B. Artificial intelligence in pediatric allergy research. European Journal of Pediatrics 2024;184(1) View
  3. Mahmood S, Hasan R, Hussain S, Adhikari R. An Interpretable and Generalizable Machine Learning Model for Predicting Asthma Outcomes: Integrating AutoML and Explainable AI Techniques. World 2025;6(1):15 View
  4. Dinh T, Wong H, Fournier-Viger P, Lisik D, Ha M, Dam H, Huynh V. Categorical data clustering: 25 years beyond K-modes. Expert Systems with Applications 2025;272:126608 View