Published on in Vol 23, No 11 (2021): November
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/29386, first published
.
Journals
- Funnell E, Spadaro B, Benacek J, Martin-Key N, Metcalfe T, Olmert T, Barton-Owen G, Bahn S. Learnings from user feedback of a novel digital mental health assessment. Frontiers in Psychiatry 2022;13 View
- Papagni G, de Pagter J, Zafari S, Filzmoser M, Koeszegi S. Artificial agents’ explainability to support trust: considerations on timing and context. AI & SOCIETY 2023;38(2):947 View
- Kopka M, Schmieding M, Rieger T, Roesler E, Balzer F, Feufel M. Determinants of Laypersons’ Trust in Medical Decision Aids: Randomized Controlled Trial. JMIR Human Factors 2022;9(2):e35219 View
- Schmieding M, Kopka M, Schmidt K, Schulz-Niethammer S, Balzer F, Feufel M. Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation. Journal of Medical Internet Research 2022;24(5):e31810 View
- Stepin I, Alonso-Moral J, Catala A, Pereira-Fariña M. An empirical study on how humans appreciate automated counterfactual explanations which embrace imprecise information. Information Sciences 2022;618:379 View
- Shen Y, Xu W, Liang A, Wang X, Lu X, Lu Z, Gao C. Online health management continuance and the moderating effect of service type and age difference: A meta-analysis. Health Informatics Journal 2022;28(3) View
- You Y, Tsai C, Li Y, Ma F, Heron C, Gui X. Beyond Self-diagnosis: How a Chatbot-based Symptom Checker Should Respond. ACM Transactions on Computer-Human Interaction 2023;30(4):1 View
- Love C. “Just the Facts Ma’am”: Moral and Ethical Considerations for Artificial Intelligence in Medicine and its Potential to Impact Patient Autonomy and Hope. The Linacre Quarterly 2023;90(4):375 View
- Wang X, Luo R, Liu Y, Chen P, Tao Y, He Y. Revealing the complexity of users’ intention to adopt healthcare chatbots: A mixed-method analysis of antecedent condition configurations. Information Processing & Management 2023;60(5):103444 View
- Subramanian H, Canfield C, Shank D. Designing explainable AI to improve human-AI team performance: A medical stakeholder-driven scoping review. Artificial Intelligence in Medicine 2024;149:102780 View
- Wetzel A, Koch R, Koch N, Klemmt M, Müller R, Preiser C, Rieger M, Rösel I, Ranisch R, Ehni H, Joos S. ‘Better see a doctor?’ Status quo of symptom checker apps in Germany: A cross-sectional survey with a mixed-methods design (CHECK.APP). DIGITAL HEALTH 2024;10 View
- Aissaoui Ferhi L, Ben Amar M, Choubani F, Bouallegue R. Enhancing diagnostic accuracy in symptom-based health checkers: a comprehensive machine learning approach with clinical vignettes and benchmarking. Frontiers in Artificial Intelligence 2024;7 View
- Wetzel A, Preiser C, Müller R, Joos S, Koch R, Henking T, Haumann H. Unveiling Usage Patterns and Explaining Usage of Symptom Checker Apps: Explorative Longitudinal Mixed Methods Study. Journal of Medical Internet Research 2024;26:e55161 View
- Kim T, Im I. Understanding users’ AI manipulation intention: An empirical investigation of the antecedents in the context of AI recommendation algorithms. Information & Management 2025;62(1):104061 View
- Cheung J, Ho S. Explainable AI and trust: How news media shapes public support for AI-powered autonomous passenger drones. Public Understanding of Science 2024 View
Books/Policy Documents
- Rezaeian O, Bayrak A, Asan O. HCI International 2024 Posters. View