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

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