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Published on in Vol 17 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69564, first published .
Diverse group discusses AI in a support group setting, with an AI brain graphic on a display.

Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Journals

  1. Asghar W, Khalid N. Precision nutrition at the crossroads: translational challenges and bottlenecks hampering the promise. Nutrition and Health 2025;31(3):801 View
  2. Haskell H, Giardina T, Dolka I, McDonald K. Ten years on: how far have we come in patient engagement in diagnosis?. Diagnosis 2025;12(4):538 View
  3. Irfan B, Boyd J, Sirvent R. When Protecting Privacy Means Protecting Health: Foreseeable Health Harms of AI Language Translation and Interpretation Technologies for Immigrant Patients. NEJM AI 2025;2(12) View
  4. Wubineh B, Deriba F, Gemeda F. Ethical concerns and strategies for implementing artificial intelligence in healthcare: a review of empirical studies. BMC Medical Ethics 2026;27(1) View
  5. Martini N, Dhaliwal N, Alipour E, Scahill S, Sajtos L. Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study. JMIR Formative Research 2026;10:e83030 View
  6. Nguyen N, Tran P. The Third Presence in the Clinic Room: How Artificial Intelligence Is Reshaping the Clinical Encounter. Mayo Clinic Proceedings: Digital Health 2026;4(2):100354 View
  7. Housni A, Shulkin A, Katz A, Giannini G, Roy-Fleming A, Nakhla M, South C, Brazeau A. Designing a Carbohydrate Counting App for Young Adults With Type 1 Diabetes: Usability Testing Interview Study. Journal of Medical Internet Research 2026;28:e86024 View
  8. Maciej Kokoszka , Michalina Chodór , Julia Maria Kuczkowska , Judyta Bordakiewicz , Zuzanna Michalska , Donata Pokorska , Julia Świechowska , Zuzanna Zarzycka , Ingrid Samberger , Magdalena Wiciak . ALGORITHMIC AUTHORITY VS. HUMAN TOUCH: A NARRATIVE REVIEW OF PATIENT TRUST AND CLINICAL AUTONOMY IN AI-ASSISTED DIAGNOSTICS. International Journal of Innovative Technologies in Social Science 2026;3(1(49)) View
  9. Giwa A. Institutional trust and AI-assisted surgery in the US: implications for ethical governance. AI and Ethics 2026;6(3) View
  10. Hou J, Zhang Z, Cheng X, Wang W. Patient Concerns Regarding Artificial Intelligence Applications in Health Care: Systematic Review and Meta-Synthesis Based on Social Ecological Theory. Journal of Medical Internet Research 2026;28:e85663 View
  11. Jakub Sałak , Wiktoria Donocik , Jakub Wrona , Piotr Tryczyński , Piotr Helbin , Aleksandra Gralec , Sebastian Ożga , Aleksandra Spirkowicz . NAVIGATING THE SOCIO-TECHNICAL SHIFT: A SYSTEMATIC REVIEW OF PATIENT TRUST, ANXIETY, AND INFORMED CONSENT IN AI-ENHANCED MAMMOGRAPHY (2022-2026). International Journal of Innovative Technologies in Social Science 2026;4(1(49)) View
  12. . AI Clinical Scribe Limitations: Scoping Review with ☸️SAIMSARA. SAIMSARA Journal 2026;1(3) View
  13. Rabinowitz A, Trauger M, Williams M. Reining In Unbridled AI Enthusiasm: Protecting the Integrity of Rehabilitation Science & Clinical Care. Archives of Physical Medicine and Rehabilitation 2026 View