Published on in Vol 25 (2023)

This is a member publication of University College London (Jisc)

Preprints (earlier versions) of this paper are available at, first published .
Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence

Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence

Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence


  1. Hogg H, Brittain K, Teare D, Talks J, Balaskas K, Keane P, Maniatopoulos G. Safety and efficacy of an artificial intelligence-enabled decision tool for treatment decisions in neovascular age-related macular degeneration and an exploration of clinical pathway integration and implementation: protocol for a multi-methods validation study. BMJ Open 2023;13(2):e069443 View
  2. Bignami E, Vittori A, Lanza R, Compagnone C, Cascella M, Bellini V. The Clinical Researcher Journey in the Artificial Intelligence Era: The PAC-MAN’s Challenge. Healthcare 2023;11(7):975 View
  3. Camaradou J, Hogg H. Commentary: Patient Perspectives on Artificial Intelligence; What have We Learned and How Should We Move Forward?. Advances in Therapy 2023;40(6):2563 View
  4. Gonzalez R, Saha A, Campbell C, Nejat P, Lokker C, Norgan A. Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities. Journal of Pathology Informatics 2024;15:100347 View
  5. Nov O, Singh N, Mann D. Putting ChatGPT’s Medical Advice to the (Turing) Test: Survey Study. JMIR Medical Education 2023;9:e46939 View
  6. Sezgin E. Artificial intelligence in healthcare: Complementing, not replacing, doctors and healthcare providers. DIGITAL HEALTH 2023;9 View
  7. Sallam M, Salim N, Barakat M, Al-Mahzoum K, Al-Tammemi A, Malaeb D, Hallit R, Hallit S. Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study. JMIR Medical Education 2023;9:e48254 View
  8. 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
  9. Wang S, Hogg H, Sangvai D, Patel M, Weissler E, Kellogg K, Ratliff W, Balu S, Sendak M. Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study. JMIR Formative Research 2023;7:e43963 View
  10. 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
  11. 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
  12. Sideris K, Weir C, Schmalfuss C, Hanson H, Pipke M, Tseng P, Lewis N, Sallam K, Bozkurt B, Hanff T, Schofield R, Larimer K, Kyriakopoulos C, Taleb I, Brinker L, Curry T, Knecht C, Butler J, Stehlik J. Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial. Journal of the American Medical Informatics Association 2024;31(4):919 View
  13. Macdonald T, Dinnes J, Maniatopoulos G, Taylor-Phillips S, Shinkins B, Hogg J, Dunbar J, Solebo A, Sutton H, Attwood J, Pogose M, Given-Wilson R, Greaves F, Macrae C, Pearson R, Bamford D, Tufail A, Liu X, Denniston A. Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study. JMIR Research Protocols 2024;13:e50568 View
  14. Canfell O, Woods L, Meshkat Y, Krivit J, Gunashanhar B, Slade C, Burton-Jones A, Sullivan C. The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis. Journal of Medical Internet Research 2024;26:e47715 View
  15. 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
  16. Maleki Varnosfaderani S, Forouzanfar M. The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century. Bioengineering 2024;11(4):337 View
  17. Khan S, Hoodbhoy Z, Raja M, Kim J, Hogg H, Manji A, Gulamali F, Hasan A, Shaikh A, Tajuddin S, Khan N, Patel M, Balu S, Samad Z, Sendak M, Ni Z. Frameworks for procurement, integration, monitoring, and evaluation of artificial intelligence tools in clinical settings: A systematic review. PLOS Digital Health 2024;3(5):e0000514 View
  18. Lee L, Salami R, Martin H, Shantharam L, Thomas K, Ashworth E, Allan E, Yung K, Pauling C, Leyden D, Arthurs O, Shelmerdine S. “How I would like AI used for my imaging”: children and young persons’ perspectives. European Radiology 2024 View
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  20. Benabed A, Bujor D, Manita Bulareanu A, Constantin Ene A. The Role of AI for Business and Companies’ Leadership and Internationalization in Globalization: A Background with Analysis. Proceedings of the International Conference on Business Excellence 2024;18(1):268 View
  21. Kumar A, Upadhyay U. Ethical Implications in AI-Based Health Care Decision Making: A Critical Analysis. AI in Precision Oncology 2024 View

Books/Policy Documents

  1. Najjar R. A Comprehensive Overview of Telemedicine [Working Title]. View