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  • Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort

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Respiratory medicine
Protocol
Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort

Authors

  • Zain Hussain Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UK PubMed articlesGoogle scholar articles
  • Syed Ahmar Shah Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UKAsthma UK Centre for Applied Research (AUKCAR), The University of Edinburgh, Edinburgh, UK PubMed articlesGoogle scholar articles
  • Mome Mukherjee Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UKAsthma UK Centre for Applied Research (AUKCAR), The University of Edinburgh, Edinburgh, UK PubMed articlesGoogle scholar articles
  • Aziz Sheikh Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UKAsthma UK Centre for Applied Research (AUKCAR), The University of Edinburgh, Edinburgh, UKDivision of Community Health Sciences, The University of Edinburgh, Edinburgh, UK PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Syed Ahmar Shah; ahmar.shah{at}ed.ac.uk
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Citation

Hussain Z, Shah SA, Mukherjee M, et al
Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort
BMJ Open 2020;10:e036099. doi: 10.1136/bmjopen-2019-036099

Publication history

  • Received November 29, 2019
  • Revised March 12, 2020
  • Accepted June 10, 2020
  • First published July 23, 2020.
Online issue publication 
February 14, 2023
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© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.