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

Formative Evaluation of Digital Health Interventions (3291) Artificial Intelligence (2185) Clinical Information and Decision Making (1953) Machine Learning (2121) Design and Usability of Clinical Software and EHRs (355) Decision Support for Health Professionals (1563) Clinical Informatics (1348)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45391, first published .
Clinical Needs Assessment of a Machine Learning–Based Asthma Management Tool: User-Centered Design Approach

Clinical Needs Assessment of a Machine Learning–Based Asthma Management Tool: User-Centered Design Approach

Clinical Needs Assessment of a Machine Learning–Based Asthma Management Tool: User-Centered Design Approach

Authors of this article:

Lu Zheng1 Author Orcid Image ;   Joshua W Ohde1 Author Orcid Image ;   Shauna M Overgaard1 Author Orcid Image ;   Tracey A Brereton1 Author Orcid Image ;   Kristelle Jose1 Author Orcid Image ;   Chung-Il Wi2, 3 Author Orcid Image ;   Kevin J Peterson1 Author Orcid Image ;   Young J Juhn2, 3, 4 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Ojha T, Patel A, Sivapragasam K, Sharma R, Vosoughi T, Skidmore B, Pinto A, Hosseini B. Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review. JMIR AI 2024;3:e57983 View
  2. Tun H, Rahman H, Naing L, Malik O. Trust in Artificial Intelligence–Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review. Journal of Medical Internet Research 2025;27:e69678 View
  3. Liu Y, Liu C, Zheng J, Xu C, Wang D. Improving Explainability and Integrability of Medical AI to Promote Health Care Professional Acceptance and Use: Mixed Systematic Review. Journal of Medical Internet Research 2025;27:e73374 View
  4. Abu-Hani A, Mansour Q, Khresat M, Alkhalili A. Applying machine learning for early-stage design decision support: a framework for enhancing designer intuition and method usability. Asian Journal of Civil Engineering 2025 View
  5. Tibble H, Garcia Iglesias J, Chung A. A qualitative interview study to investigate opportunities for improvement in routine asthma care using a clinical decision support system. Scientific Reports 2025;15(1) View
  6. Myers L, Brereton T, Overgaard S, Greenwood J, Zheng L, Ohde J, Spiten M, Kathy Ihrke R, Lang K, Peterson K, Hawley S, Beenken M, Malik M, Bublitz J, Galloway T, Wilkes Q, Shrader D, Mercado L, Park M, Arteta M, Hartz M, Fladager-Muth J, Quam M, Perrigo T, Loufek T, Khurana A, Kshatriya B, Sharma D, Le-Rademacher J, Wi C, Nordlund B, Juhn Y. Pediatric asthma management via integration of a remote spirometry device into an EHR-based artificial intelligence-powered clinical decision support system: A feasibility pragmatic clinical trial. Contemporary Clinical Trials 2026;161:108209 View