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

JMIR Theme Issue: COVID-19 Special Issue (2493) JMIR Theme Issue: COVID-19 Special Issue (2493) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1530) Clinical Information and Decision Making (1641) Artificial Intelligence (1714) Decision Support for Health Professionals (1336) Outbreak and Pandemic Preparedness and Management (1779)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22841, first published .
Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment

Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment

Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment

Authors of this article:

Taoran Liu1, 2 Author Orcid Image ;   Winghei Tsang1 Author Orcid Image ;   Fengqiu Huang1 Author Orcid Image ;   Oi Ying Lau1 Author Orcid Image ;   Yanhui Chen1 Author Orcid Image ;   Jie Sheng1 Author Orcid Image ;   Yiwei Guo3 Author Orcid Image ;   Babatunde Akinwunmi4, 5 Author Orcid Image ;   Casper JP Zhang6 Author Orcid Image ;   Wai-Kit Ming1 Author Orcid Image
Article Authors Cited by (14) Tweetations (4) Metrics

Journals

  1. Haleem A, Javaid M, Singh R, Suman R. Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic. Sustainable Operations and Computers 2021;2:71 View
  2. Haghani M, Bliemer M, de Bekker-Grob E. Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields. Journal of Choice Modelling 2022;44:100371 View
  3. Chen P, Lu Y, Kang Y, Chang C. The Accuracy of Artificial Intelligence in the Endoscopic Diagnosis of Early Gastric Cancer: Pooled Analysis Study. Journal of Medical Internet Research 2022;24(5):e27694 View
  4. Yi-No Kang E, Chen D, Chen Y. Associations between literacy and attitudes toward artificial intelligence–assisted medical consultations: The mediating role of perceived distrust and efficiency of artificial intelligence. Computers in Human Behavior 2023;139:107529 View
  5. Chew H, Achananuparp P. Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review. Journal of Medical Internet Research 2022;24(1):e32939 View
  6. Mühlbacher A, Sadler A, Jordan Y. Population preferences for non-pharmaceutical interventions to control the SARS-CoV-2 pandemic: trade-offs among public health, individual rights, and economics. The European Journal of Health Economics 2022;23(9):1483 View
  7. Tanaka M, Matsumura S, Bito S. Roles and Competencies of Doctors in Artificial Intelligence Implementation: Qualitative Analysis Through Physician Interviews. JMIR Formative Research 2023;7:e46020 View
  8. 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
  9. 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
  10. Liou J, Vo T. Exploring the Relationships among Factors Influencing Healthcare Chatbot Adoption. Sustainability 2024;16(12):5050 View
  11. Latt P, Soe N, King A, Lee D, Phillips T, Xu X, Chow E, Fairley C, Zhang L, Ong J. Preferences for attributes of an artificial intelligence-based risk assessment tool for HIV and sexually transmitted infections: a discrete choice experiment. BMC Public Health 2024;24(1) View
  12. Li W, Liu X. Anxiety about artificial intelligence from patient and doctor-physician. Patient Education and Counseling 2025;133:108619 View
  13. Ding X, Shang B, Xie C, Xin J, Yu F. Artificial intelligence in the COVID-19 pandemic: balancing benefits and ethical challenges in China’s response. Humanities and Social Sciences Communications 2025;12(1) View
  14. Ma X, Liu T, Yu J, Gao Y, LEUNG C, Liang S, Akinwunmi B, Liu X, Huang J, Zhang C, Ming W. Exploring parental preferences for childhood obesity prevention program in China: a discrete choice experiment. BMC Public Health 2025;25(1) View