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

Formative Evaluation of Digital Health Interventions (2491) Pulmonology, COPD (145) Asthma Education and Self-Management in Childhood and Adolescence (71) Artificial Intelligence (1421) Quality/Credibility of eHealth Information and Trust Issues (544) Demographics of Users, Social & Digital Divide (760) Machine Learning (1501) Clinical Informatics (1050) Equity and Digital Divide (233)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59811, first published .
Perceptions Toward Using Artificial Intelligence and Technology for Asthma Attack Risk Prediction: Qualitative Exploration of Māori Views

Perceptions Toward Using Artificial Intelligence and Technology for Asthma Attack Risk Prediction: Qualitative Exploration of Māori Views

Perceptions Toward Using Artificial Intelligence and Technology for Asthma Attack Risk Prediction: Qualitative Exploration of Māori Views

Authors of this article:

Widana Kankanamge Darsha Jayamini1, 2 Author Orcid Image ;   Farhaan Mirza1 Author Orcid Image ;   Marie-Claire Bidois-Putt3 Author Orcid Image ;   M Asif Naeem4 Author Orcid Image ;   Amy Hai Yan Chan3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Widana Kankanamge Darsha Jayamini   1, 2 , BSc ;   Farhaan Mirza   1 , BSE, MSE, PhD ;   Marie-Claire Bidois-Putt   3 ;   M Asif Naeem   4 , BSc, MSc, MS, PhD ;   Amy Hai Yan Chan   3 , BPharm(Hons), PhD

1 Department of Computer Science, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

2 Department of Software Engineering, Faculty of Computing and Technology, University of Kelaniya, Kelaniya, Sri Lanka

3 School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand

4 Department of Data Science & Artificial Intelligence, National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan

Corresponding Author:

  • Widana Kankanamge Darsha Jayamini, BSc
  • Department of Computer Science
  • School of Engineering, Computer and Mathematical Sciences
  • Auckland University of Technology
  • Building WZ, Level 8
  • 6th St Paul Street
  • Auckland, 1010
  • New Zealand
  • Phone: 64 210504680
  • Email: darsha.jayamini@autuni.ac.nz