Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28916, first published .
General Practitioners’ Attitudes Toward Artificial Intelligence–Enabled Systems: Interview Study

General Practitioners’ Attitudes Toward Artificial Intelligence–Enabled Systems: Interview Study

General Practitioners’ Attitudes Toward Artificial Intelligence–Enabled Systems: Interview Study

Journals

  1. Rashid A. Yonder: Primary aldosteronism, artificial intelligence, irritable bowel syndrome, and financial toxicity. British Journal of General Practice 2022;72(724):534 View
  2. Fraile Navarro D, Kocaballi A, Dras M, Berkovsky S. Collaboration, not Confrontation: Understanding General Practitioners’ Attitudes Towards Natural Language and Text Automation in Clinical Practice. ACM Transactions on Computer-Human Interaction 2023;30(2):1 View
  3. Stanley A, Edwards T, Jaere M, Lex J, Jones G. An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: A proof-of-concept study. DIGITAL HEALTH 2023;9:205520762311521 View
  4. D’Hondt E, Ashby T, Chakroun I, Koninckx T, Wuyts R. Identifying and evaluating barriers for the implementation of machine learning in the intensive care unit. Communications Medicine 2022;2(1) View
  5. Chen M, Zhang B, Cai Z, Seery S, Gonzalez M, Ali N, Ren R, Qiao Y, Xue P, Jiang Y. Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey. Frontiers in Medicine 2022;9 View
  6. Frisinger A, Papachristou P. The voice of healthcare: introducing digital decision support systems into clinical practice - a qualitative study. BMC Primary Care 2023;24(1) View
  7. Thirunavukarasu A, Hassan R, Mahmood S, Sanghera R, Barzangi K, El Mukashfi M, Shah S. Trialling a Large Language Model (ChatGPT) in General Practice With the Applied Knowledge Test: Observational Study Demonstrating Opportunities and Limitations in Primary Care. JMIR Medical Education 2023;9:e46599 View
  8. Chen M, Zhang B, Cai Z, Seery S, Mendez M, Ali N, Ren R, Qiao Y, Xue P, Jiang Y. Physician and Medical Student Attitudes Toward Clinical Artificial Intelligence: A Systematic Review with Cross-Sectional Survey. SSRN Electronic Journal 2022 View
  9. Diel S, Doctor E, Reith R, Buck C, Eymann T. Examining supporting and constraining factors of physicians’ acceptance of telemedical online consultations: a survey study. BMC Health Services Research 2023;23(1) View
  10. Hamedani Z, Moradi M, Kalroozi F, Manafi Anari A, Jalalifar E, Ansari A, Aski B, Nezamzadeh M, Karim B. Evaluation of acceptance, attitude, and knowledge towards artificial intelligence and its application from the point of view of physicians and nurses: A provincial survey study in Iran: A cross‐sectional descriptive‐analytical study. Health Science Reports 2023;6(9) View
  11. Bergdahl J, Latikka R, Celuch M, Savolainen I, Soares Mantere E, Savela N, Oksanen A. Self-determination and attitudes toward artificial intelligence: Cross-national and longitudinal perspectives. Telematics and Informatics 2023;82:102013 View
  12. Hogg H, Al-Zubaidy M, Keane P, Hughes G, Beyer F, Maniatopoulos G. Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research. Frontiers in Health Services 2023;3 View
  13. Wewetzer L, Held L, Goetz K, Steinhäuser J. Determinants of the implementation of artificial intelligence-based screening for diabetic retinopathy—a cross-sectional study with general practitioners in Germany. DIGITAL HEALTH 2023;9:205520762311766 View
  14. Kenny R, Fischhoff B, Davis A, Canfield C. Improving Social Bot Detection Through Aid and Training. Human Factors: The Journal of the Human Factors and Ergonomics Society 2023 View
  15. Hummelsberger P, Koch T, Rauh S, Dorn J, Lermer E, Raue M, Hudecek M, Schicho A, Colak E, Ghassemi M, Gaube S. Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study. JMIR AI 2023;2:e47353 View
  16. Chen Y, Wu Z, Wang P, Xie L, Yan M, Jiang M, Yang Z, Zheng J, Zhang J, Zhu J. Radiology Residents’ Perceptions of Artificial Intelligence: Nationwide Cross-Sectional Survey Study. Journal of Medical Internet Research 2023;25:e48249 View
  17. Helenason J, Ekström C, Falk M, Papachristou P. Exploring the feasibility of an artificial intelligence based clinical decision support system for cutaneous melanoma detection in primary care – a mixed method study. Scandinavian Journal of Primary Health Care 2024;42(1):51 View
  18. Kulkov I, Kulkova J, Leone D, Rohrbeck R, Menvielle L. Stand-alone or run together: artificial intelligence as an enabler for other technologies. International Journal of Entrepreneurial Behavior & Research 2023 View
  19. Townsend B, Plant K, Hodge V, Ashaolu O, Calinescu R. Medical practitioner perspectives on AI in emergency triage. Frontiers in Digital Health 2023;5 View
  20. Stewart J, Freeman S, Eroglu E, Dumitrascu N, Lu J, Goudie A, Sprivulis P, Akhlaghi H, Tran V, Sanfilippo F, Celenza A, Than M, Fatovich D, Walker K, Dwivedi G. Attitudes towards artificial intelligence in emergency medicine. Emergency Medicine Australasia 2024;36(2):252 View
  21. Čartolovni A, Malešević A, Poslon L. Critical analysis of the AI impact on the patient–physician relationship: A multi-stakeholder qualitative study. DIGITAL HEALTH 2023;9 View
  22. Koebe P, Bohnet-Joschko S. What’s next in hospital digitization? A Delphi-based scenario study. European Journal of Futures Research 2023;11(1) View
  23. 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
  24. Giddings R, Joseph A, Callender T, Janes S, van der Schaar M, Sheringham J, Navani N. Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review. The Lancet Digital Health 2024;6(2):e131 View
  25. Allen M, Webb S, Mandvi A, Frieden M, Tai-Seale M, Kallenberg G. Navigating the doctor-patient-AI relationship - a mixed-methods study of physician attitudes toward artificial intelligence in primary care. BMC Primary Care 2024;25(1) View
  26. Gunathilaka N, Gooden T, Cooper J, Flanagan S, Marshall T, Haroon S, D’Elia A, Crowe F, Jackson T, Nirantharakumar K, Greenfield S. Perceptions on artificial intelligence-based decision-making for coexisting multiple long-term health conditions: protocol for a qualitative study with patients and healthcare professionals. BMJ Open 2024;14(2):e077156 View
  27. Gültekin M, Şahin M. The use of artificial intelligence in mental health services in Turkey: What do mental health professionals think?. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2024;18(1) View
  28. 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
  29. Frisinger A, Papachristou P. Bridging the voice of healthcare to digital transformation in practice – a holistic approach. BMC Digital Health 2024;2(1) View
  30. Papachristou P, Söderholm M, Pallon J, Taloyan M, Polesie S, Paoli J, Anderson C, Falk M. Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial. British Journal of Dermatology 2024;191(1):125 View
  31. Ling Kuo R, Freethy A, Smith J, Hill R, C J, Jerome D, Harriss E, Collins G, Tutton E, Furniss D. Stakeholder perspectives towards diagnostic artificial intelligence: a co-produced qualitative evidence synthesis. eClinicalMedicine 2024;71:102555 View
  32. Hennrich J, Ritz E, Hofmann P, Urbach N. Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study. BMC Health Services Research 2024;24(1) View
  33. 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
  34. Diaz-Asper C, Chandler C, Elvevåg B, Thomas K. Cognitive Screening for Mild Cognitive Impairment: Clinician Perspectives on Current Practices and Future Directions. Journal of Alzheimer's Disease 2024;99(3):869 View