Published on in Vol 27 (2025)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/66986, first published
.

Journals
- Aftab N. Artificial Intelligence in Obstetrics and Gynaecology: Advancing Precision and Personalised Care. Cureus 2025 View
- Livieratos A, Kagadis G, Gogos C, Akinosoglou K. AI Methods Tailored to Influenza, RSV, HIV, and SARS-CoV-2: A Focused Review. Pathogens 2025;14(8):748 View
- Johnson M. AI and the urgency for proactive regulation. AI and Ethics 2025;5(6):6265 View
- Takahashi G, von Liechti L, Tarshizi E. Quo Vadis, AI-Empowered Doctor?. JMIR Medical Education 2025;11:e70079 View
- da Costa R, Pereira M, Pereira A, Canas J, Correia R, Dimande C. Factors Influencing the Adoption of Artificial Intelligence in Healthcare: A Study on the Role of Knowledge and Benefits in Clinical and Managerial Decision-Making. Businesses 2025;5(4):44 View
- Çakan K, İpek İ. From lecture hall to clinic: dental students’ AI readiness and anxiety across educational stages. BMC Medical Education 2025;25(1) View
- Barberis M. Shortage of Pathologists: a candid narrative. Pathologica 2025;117(4):452 View
- Sani H, Mobaraki M, Sholibor A, Fallah S, Abdi F, Hasannezhad M, Jandaghian-Bidgoli M. Adoption of artificial intelligence in primary health care: systematic synthesis of stakeholder perspectives. BMC Primary Care 2026;27(1) View
- Abreu M, de Brito Duarte R, Neves B, Silva N, Santos R, Campos J. AI Assistance in Medical Decision-Making: The Role of Recommendations and Explanations in Simulated Clinical Cases. ACM Transactions on Computing for Healthcare 2026 View
- Lee J, Min Y, Yim J, Park K, Yune S. Mediating effect of technostress on the relationship between artificial intelligence literacy and attitude toward digital technology among health professions students: a structural equation modeling approach. Journal of Yeungnam Medical Science 2025;43:7 View
- Zeng Q, Zhu J, Wang Y, Su S, Huang Y. Artificial intelligence self-efficacy and attitudes among nursing students: a multicenter network analysis of educational stratification. BMC Medical Education 2026;26(1) View
- Li Q, Liu H, Wang J. Value of Machine Learning Models for Cell-Free DNA-Based Multi-Cancer Early Detection: A Systematic Review and Meta-Analysis. Technology in Cancer Research & Treatment 2026;25 View
- Yuan C, Lee Y. How cultural cognition affects trust and perceived quality of AI explanations. Computers in Human Behavior Reports 2026;22:101021 View
- Arvai N, Meskó B, Katonai G. How Generative AI Will Impact The Mental Health of Medical Students: A Scenario Analysis (Preprint). JMIR Medical Education 2025 View
- ALruwaili B, Alruwili A, Alruwaili A, Alruwaili H, Almutairi N, Alruwaili T, Alsirhani B, Thirunavukkarasu A, AL-Ruwaili H. Assessing Primary Care Physicians’ Readiness for AI-Based Adaptive Learning: Perceptions, Barriers, and Learning Needs in Northern Saudi Arabia. Healthcare 2026;14(7):865 View
- Brandtzaeg P, Skjuve M, Følstad A. AI aversion? Effects of author disclosure on young people’s perceptions of mental health advice. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2026;20(2) View
- Xu K, Wu Q, Wang M. Deconstructing Ambivalence Toward AI: Development and Validation of a Five-Dimension Scale (AAAIS). International Journal of Human–Computer Interaction 2026:1 View
- Mendlovic S, Frankova I, Vermetten E, Wasserman D, Schulze T, Falkai P, Fountoulakis K, Adorjan K, Uchida H, Fruchter E, Gobbi G, Zohar J. Responsible artificial intelligence integration framework for psychiatric guidelines. International Journal of Neuropsychopharmacology 2026;29(4) View
- May P, Brookman-May S, Garrahy E, von Büren J. Sequencing AI Automation and Data Interoperability in Oncology: A Scenario-Planning Framework Coupled With Discrete-Event Simulation (Preprint). Journal of Medical Internet Research 2026 View
Books/Policy Documents
Conference Proceedings
- Ehsan U, Passi S, Saha K, McNutt T, Riedl M, Alcorn S. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. From Future of Work to Future of Workers: Addressing Asymptomatic AI Harms to Foster Dignified Human-AI Interaction View
