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Published on in Vol 11 (2024)

This is a member publication of National University of Singapore

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50939, first published .
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Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence–Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study

Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence–Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study

Journals

  1. He Z, Li W. AI-Driven Management of Type 2 Diabetes in China: Opportunities and Challenges. Diabetes, Metabolic Syndrome and Obesity 2025;Volume 18:85 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. González-Rivas J, Seyedi S, Mechanick J. Artificial Intelligence Enabled Lifestyle Medicine in Diabetes Care: A Narrative Review. American Journal of Lifestyle Medicine 2025 View
  4. Parsons C, Zuiderwijk A, Orchard N, Oosterhoff J, de Reuver M. Task-Technology Fit of Artificial Intelligence-based clinical decision support systems: a review of qualitative studies. BMC Medical Informatics and Decision Making 2025;25(1) View
  5. Li W, Li L. Artificial intelligence in mobile health applications: A comprehensive review of its role in diabetes care. World Journal of Methodology 2026;16(1) View
  6. Kon M, Abisheganaden J, Ang G. How clinicians should prioritise the use of artificial intelligence in Singapore’s healthcare system: Correspondence. Annals of the Academy of Medicine Singapore 2026;55(5):289 View
  7. Goh H, Khuon D, Ung M, Oy S, Dary C, Khim C, Chhay S, Lee Y, Kim R, Yi S, Saphonn V. i-MoMCARE: AI-enabled mobile app for maternal and child health care in Cambodia – a pilot implementation and evaluation study. BMJ Health & Care Informatics 2026;33(1):e101691 View
  8. Hu H, LI R, Yin Y, Liu Y, Wang X. Human factors engineering in intelligent medical devices: paradigm evolution, core issues and frontier prospects. Frontiers in Industrial Engineering 2026;4 View
  9. Fernández-Concha R, Solórzano Muñante M. Heuristic or Algorithmic Thinking? Assessing Generative AI’s Impact on Human Decision-Making. A Literature Review. Applied Artificial Intelligence 2026;40(1) View
  10. Martínez-Martínez H, Martínez-Alfonso J, Sánchez-Rojo-Huertas B, Visier-Alfonso M, Sebastián-Valles F, Díez-Fernández A, Pérez-Moreno A, Martínez-Vizcaíno V. Stakeholder Perspectives on the Integration of AI in Diabetes Care: Systematic Review of Qualitative Studies. Journal of Medical Internet Research 2026;28:e105329 View
  11. Park H. Human–artificial intelligence collaboration in emergency medical services: from diagnostic algorithms to shared decision support. Clinical and Experimental Emergency Medicine 2026;13(3):350 View

Books/Policy Documents

  1. Karim A, Ghaffar F, Xu W, Furtado N, Burns C. HCI International 2026 Posters. View
  2. Asrifan A, Patinrosi N, Sahabuddin S. Cybersecurity, AI Collaboration, and Software Practice for Healthcare. View