Machine learning classification approach for asthma prediction models in children
Author:
Funder
Funding
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology
Link
https://link.springer.com/content/pdf/10.1007/s12553-023-00732-8.pdf
Reference35 articles.
1. World Health Organization asthma. Fact sheet. retrieved from http://www.who.int/respiratory/asthma/en/. Accessed Feb 2020.
2. Kikidis D, Votis K, Tzovaras D. MyAirCoach: Designing a mobile application for the education of patients regarding asthma disease. In: 2015 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL). IEEE; 2015. p. 373–377.
3. Kothalawala DM, Kadalayil L, Weiss VB, et al. Prediction models for childhood asthma: a systematic review. Pediatr Allergy Immunol. 2020;31(6):616–27.
4. Reddel HK, Bateman ED, Becker A, et al. A summary of the new GINA strategy: a roadmap to asthma control. Eur Respir J. 2015;46(3):622–39.
5. Luo G, Nkoy FL, Stone BL, Schmick D, Johnson MD. A systematic review of predictive models for asthma development in children. BMC Med Inform Decis Mak. 2015;15(1):1–16.
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