Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at, first published .
Patients’ Perceptions Toward Human–Artificial Intelligence Interaction in Health Care: Experimental Study

Patients’ Perceptions Toward Human–Artificial Intelligence Interaction in Health Care: Experimental Study

Patients’ Perceptions Toward Human–Artificial Intelligence Interaction in Health Care: Experimental Study


  1. Morrow E, Zidaru T, Ross F, Mason C, Patel K, Ream M, Stockley R. Artificial intelligence technologies and compassion in healthcare: A systematic scoping review. Frontiers in Psychology 2023;13 View
  2. Fritsch S, Blankenheim A, Wahl A, Hetfeld P, Maassen O, Deffge S, Kunze J, Rossaint R, Riedel M, Marx G, Bickenbach J. Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. DIGITAL HEALTH 2022;8:205520762211167 View
  3. Jeyakumar T, Younus S, Zhang M, Clare M, Charow R, Karsan I, Dhalla A, Al-Mouaswas D, Scandiffio J, Aling J, Salhia M, Lalani N, Overholt S, Wiljer D. Preparing for an Artificial Intelligence–Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings. JMIR AI 2023;2:e40973 View
  4. Sebastian G, George A, Jackson Jr G. Persuading Patients Using Rhetoric to Improve Artificial Intelligence Adoption: Experimental Study. Journal of Medical Internet Research 2023;25:e41430 View
  5. Wilson N. CORR Insights®: Can a Deep Learning Algorithm Improve Detection of Occult Scaphoid Fractures in Plain Radiographs? A Clinical Validation Study. Clinical Orthopaedics & Related Research 2023;481(9):1836 View
  6. Bedi A, Al Masri M, Al Hennawi H, Qadir S, Ottman P. The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch. Cureus 2023 View
  7. Huo W, Yuan X, Li X, Luo W, Xie J, Shi B. Increasing acceptance of medical AI: The role of medical staff participation in AI development. International Journal of Medical Informatics 2023;175:105073 View
  8. Thirunavukarasu A. Large language models will not replace healthcare professionals: curbing popular fears and hype. Journal of the Royal Society of Medicine 2023;116(5):181 View
  9. Steerling E, Siira E, Nilsen P, Svedberg P, Nygren J. Implementing AI in healthcare—the relevance of trust: a scoping review. Frontiers in Health Services 2023;3 View
  10. Kheirinejad S, Visuri A, Suryanarayana S, Hosio S. Exploring mHealth applications for self-management of chronic low back pain: A survey of features and benefits. Heliyon 2023;9(6):e16586 View
  11. Ibba S, Tancredi C, Fantesini A, Cellina M, Presta R, Montanari R, Papa S, Alì M. How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders. European Journal of Radiology 2023;165:110917 View
  12. Marks R. Artificial intelligence and rehabilitation: what’s new and promising. International Physical Medicine & Rehabilitation Journal 2023;8(2):135 View
  13. Nagar R, Quirk H, Anderson P. User experiences of college students using mental health applications to improve self-care: Implications for improving engagement. Internet Interventions 2023;34:100676 View
  14. Zhang Y, Doyle T. Integrating intention-based systems in human-robot interaction: a scoping review of sensors, algorithms, and trust. Frontiers in Robotics and AI 2023;10 View
  15. Wang B, Asan O, Mansouri M. Perspectives of Patients With Chronic Diseases on Future Acceptance of AI–Based Home Care Systems: Cross-Sectional Web-Based Survey Study. JMIR Human Factors 2023;10:e49788 View
  16. Kumar D, Ingole A, Choudhari S. Towards Ideal Health Ecosystem With Artificial Intelligence-Driven Medical Services in India: An Overview. Cureus 2023 View
  17. Ferro M, Falagario U, Barone B, Maggi M, Crocetto F, Busetto G, Giudice F, Terracciano D, Lucarelli G, Lasorsa F, Catellani M, Brescia A, Mistretta F, Luzzago S, Piccinelli M, Vartolomei M, Jereczek-Fossa B, Musi G, Montanari E, Cobelli O, Tataru O. Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement. Diagnostics 2023;13(13):2308 View
  18. Li L, Haley L, Boyd A, Bernstam E. Technical/Algorithm, Stakeholder, and Society (TASS) barriers to the application of artificial intelligence in medicine: A systematic review. Journal of Biomedical Informatics 2023;147:104531 View
  19. Busch F, Adams L, Bressem K. Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education. Medical Science Educator 2023;33(4):1007 View
  20. Tang L, Li J, Fantus S. Medical artificial intelligence ethics: A systematic review of empirical studies. DIGITAL HEALTH 2023;9 View
  21. Holm S, Ploug T, Fiaschetti M. Population preferences for AI system features across eight different decision-making contexts. PLOS ONE 2023;18(12):e0295277 View
  22. Alanzi T, Almahdi R, Alghanim D, Almusmili L, Saleh A, Alanazi S, Alshobaki K, Attar R, Al Qunais A, Alzahrani H, Alshehri R, Sulail A, Alblwi A, Alanzi N, Alanzi N. Factors Affecting the Adoption of Artificial Intelligence-Enabled Virtual Assistants for Leukemia Self-Management. Cureus 2023 View
  23. Cai Z, He H, Huo W, Xu X. More Unique, More Accepting? Integrating Sense of Uniqueness, Perceived Knowledge, and Perceived Empathy with Acceptance of Medical Artificial Intelligence. International Journal of Human–Computer Interaction 2023:1 View
  24. Bhandarkar S, Tsutsumi A, Schneider E, Ong C, Paredes L, Brackett A, Ahuja V. Emergent Applications of Machine Learning for Diagnosing and Managing Appendicitis: A State-of-the-Art Review. Surgical Infections 2024;25(1):7 View
  25. Sassi Z, Hahn M, Eickmann S, Herrmann-Johns A, Tretter M. Beyond algorithmic trust: interpersonal aspects on consent delegation to LLMs. Journal of Medical Ethics 2024;50(2):139 View
  26. Gavette H, McDonald C, Kostick-Quenet K, Mullen A, Najafi B, Finco M. Advances in prosthetic technology: a perspective on ethical considerations for development and clinical translation. Frontiers in Rehabilitation Sciences 2024;4 View
  27. Evans R, Bryant L, Russell G, Absolom K. Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review. International Journal of Medical Informatics 2024;183:105342 View
  28. Mani Z, Chouk I. Résistance initiale du consommateur aux technologies autonomes de l’Intelligence Artificielle Médicale : une approche par les préoccupations liées à la santé. Décisions Marketing 2024;N° 112(4):7 View
  29. Ng J, Cramer H, Lee M, Moher D. Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare. Integrative Medicine Research 2024;13(1):101024 View
  30. Fazakarley C, Breen M, Thompson B, Leeson P, Williamson V. Beliefs, experiences and concerns of using artificial intelligence in healthcare: A qualitative synthesis. DIGITAL HEALTH 2024;10 View
  31. Wong C, O’Byrne C, Taribagil P, Liu T, Antaki F, Keane P. Comparing code-free and bespoke deep learning approaches in ophthalmology. Graefe's Archive for Clinical and Experimental Ophthalmology 2024 View
  32. Nasir S, Khan R, Bai S. Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond. IEEE Access 2024;12:31014 View
  33. Frost E, Bosward R, Aquino Y, Braunack-Mayer A, Carter S. Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods. International Journal of Medical Informatics 2024;186:105417 View
  34. Yang Y, Ngai E, Wang L. Resistance to artificial intelligence in health care: Literature review, conceptual framework, and research agenda. Information & Management 2024;61(4):103961 View
  35. Guo S, Li R, Li G, Chen W, Huang J, He L, Ma Y, Wang L, Zheng H, Tian C, Zhao Y, Pan X, Wan H, Liu D, Li Z, Lei J. Comparing ChatGPT's and Surgeon's Responses to Thyroid-related Questions From Patients. The Journal of Clinical Endocrinology & Metabolism 2024 View
  36. Deriu V, Pozharliev R, De Angelis M. How trust and attachment styles jointly shape job candidates’ AI receptivity. Journal of Business Research 2024;179:114717 View
  37. Cvetkovic A, Savela N, Latikka R, Oksanen A, Chakraborty P. Do We Trust Artificially Intelligent Assistants at Work? An Experimental Study. Human Behavior and Emerging Technologies 2024;2024:1 View
  38. Ejdys J, Czerwińska M, Ginevičius R. Social acceptance of artificial intelligence (AI) application for improving medical service diagnostics. Human Technology 2024;20(1):155 View
  39. Wang B, Asan O, Liao T, Mansouri M. The Future Role of Clinical Artificial Intelligence: View of Chronic Patients. IEEE Transactions on Technology and Society 2024;5(1):71 View
  40. Krieger J, Bouder F, Wibral M, Almeida R. A systematic literature review on risk perception of Artificial Narrow Intelligence. Journal of Risk Research 2024:1 View

Books/Policy Documents

  1. Saxena A, Chauhan S, Singh H, Chauhan U, Kumari P. Infrastructure Possibilities and Human-Centered Approaches With Industry 5.0. View
  2. Durrah O, Aldhmour F, El-Maghraby L, Chakir A. Engineering Applications of Artificial Intelligence. View
  3. Zaabi A, Padela A. Digital Healthcare in Asia and Gulf Region for Healthy Aging and More Inclusive Societies. View