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

Theme Issue (2023): AI and Human Factors—Towards Successful Application of AI in Health Care (14) Quality/Credibility of eHealth Information and Trust Issues (588) Artificial Intelligence (1660) Ethics, Privacy, and Legal Issues (539) Security and Privacy of mHealth and uHealth (142)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47031, first published .
Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study

Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study

Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study

Authors of this article:

Daria Shevtsova1, 2 Author Orcid Image ;   Anam Ahmed1 Author Orcid Image ;   Iris W A Boot1 Author Orcid Image ;   Carmen Sanges3 Author Orcid Image ;   Michael Hudecek3 Author Orcid Image ;   John J L Jacobs4 Author Orcid Image ;   Simon Hort5 Author Orcid Image ;   Hubertus J M Vrijhoef1 Author Orcid Image
Article Authors Cited by (14) Tweetations (3) Metrics

Journals

  1. Zuhair Dahham Hammood . Artificial Intelligence in Applied Medicine. Barw Medical Journal 2023 View
  2. Gholizadeh N, Rokni G, Babaei M. Advantages and Disadvantages of Using AI in Dermatology. Dermatological Reviews 2024;5(4) View
  3. Pham T, Teh M, Chatzopoulou D, Holmes S, Coulthard P. Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions. Current Oncology 2024;31(9):5255 View
  4. Bukke S, Komarla Kumarachari R, Komarla Rajasekhar E, Dudekula J, Kamati M. Computational intelligence techniques for achieving sustainable development goals in female cancer care. Discover Sustainability 2024;5(1) View
  5. Haga S. Artificial intelligence, medications, pharmacogenomics, and ethics. Pharmacogenomics 2024;25(14-15):611 View
  6. Varghese M, Sharma P, Patwardhan M. Public Perception on Artificial Intelligence–Driven Mental Health Interventions: Survey Research. JMIR Formative Research 2024;8:e64380 View
  7. Chen H, Alfred M, Brown A, Atinga A, Cohen E. Intersection of Performance, Interpretability, and Fairness in Neural Prototype Tree for Chest X-Ray Pathology Detection: Algorithm Development and Validation Study. JMIR Formative Research 2024;8:e59045 View
  8. Dixit K, Rai B, Majhi G, Paudel R, Dhital R, Acharya S, Budhathoki G, Poudel P, Gurung S, Subedi B, Lamsal P, Pudasaini U, Small P, Meier P, Annerstedt K, Caws M. Healthcare providers’ and community stakeholders’ perception of using drones for tuberculosis diagnosis in Nepal: an exploratory qualitative study. BMC Health Services Research 2024;24(1) View
  9. De Marco E, Virga M, Torresi M, Catellani S, Pingani L, Ferrazzi G. "Should I trust or Should I not?" A Survey to measure AI Confidence Levels Among Students of the bachelor's degree in Psychiatric Rehabilitation Techniques and Psychiatry Residents. Introduction. RIVISTA SPERIMENTALE DI FRENIATRIA 2024;148(3):45 View
  10. Saraiva M, Ribeiro T, Agudo B, Afonso J, Mendes F, Martins M, Cardoso P, Mota J, Almeida M, Costa A, Gonzalez Haba Ruiz M, Widmer J, Moura E, Javed A, Manzione T, Nadal S, Barroso L, de Parades V, Ferreira J, Macedo G. Evaluating ChatGPT-4 for the Interpretation of Images from Several Diagnostic Techniques in Gastroenterology. Journal of Clinical Medicine 2025;14(2):572 View
  11. Singh R, Kim J, Glassy E, Dash R, Brodsky V, Seheult J, de Baca M, Gu Q, Hoekstra S, Pritt B. Introduction to Generative Artificial Intelligence: Contextualizing the Future. Archives of Pathology & Laboratory Medicine 2025;149(2):112 View
  12. Stroop A, Stroop T, Zawy Alsofy S, Wegner M, Nakamura M, Stroop R. Assessing GPT‐4's accuracy in answering clinical pharmacological questions on pain therapy. British Journal of Clinical Pharmacology 2025 View
  13. Hildt E. What Is the Role of Explainability in Medical Artificial Intelligence? A Case-Based Approach. Bioengineering 2025;12(4):375 View
  14. Chen H, Cohen E, Alfred M. Examining the development, effectiveness, and limitations of computer-aided diagnosis systems for retained surgical items detection: a systematic review. Ergonomics 2025:1 View