Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80898, first published .
AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration

AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration

AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration

Journals

  1. Palm E, Manikantan A, Mahal H, Belwadi S, Pepin M. Assessing the quality of AI-generated clinical notes: validated evaluation of a large language model ambient scribe. Frontiers in Artificial Intelligence 2025;8 View
  2. Scott I, Cresswell K, Williams R, van der Vegt A. How can we promote greater adoption of AI in healthcare?. BMJ Quality & Safety 2025:bmjqs-2025-019405 View
  3. Leiserowitz G, Mansfield J, MacDonald S, Jost M. Patient Attitudes Toward Ambient Voice Technology: Preimplementation Patient Survey in an Academic Medical Center. JMIR Medical Informatics 2025;13:e77901 View
  4. Coiera E, Fraile-Navarro D. AI Scribes: Are We Measuring What Matters?. JMIR Medical Informatics 2026;14:e89337 View
  5. Atiku S, Olakotan O, Owolanke K. Usability‐Related Barriers and Facilitators Influencing the Adoption and Use of AI Scribes in Healthcare: A Scoping Review. Journal of Evaluation in Clinical Practice 2026;32(1) View
  6. Ferreira Santos J, Dores H. Large Language Models in Cardiovascular Prevention: A Narrative Review and Governance Framework. Diagnostics 2026;16(3):390 View

Books/Policy Documents

  1. Hirosawa T. Artificial Intelligence in Medical Diagnostics. View