Published on in Vol 8, No 2 (2021): Apr-Jun

Preprints (earlier versions) of this paper are available at, first published .
Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Authors of this article:

Onur Asan1 Author Orcid Image ;   Avishek Choudhury1 Author Orcid Image


  1. Feng J, Phillips R, Malenica I, Bishara A, Hubbard A, Celi L, Pirracchio R. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. npj Digital Medicine 2022;5(1) View
  2. Hedlund M. Distribution of Forward-Looking Responsibility in the EU Process on AI Regulation. Frontiers in Human Dynamics 2022;4 View
  3. Sibbald M, Abdulla B, Keuhl A, Norman G, Monteiro S, Sherbino J. Electronic Diagnostic Support in Emergency Physician Triage: Qualitative Study With Thematic Analysis of Interviews. JMIR Human Factors 2022;9(3):e39234 View
  4. Vasey B, Nagendran M, Campbell B, Clifton D, Collins G, Denaxas S, Denniston A, Faes L, Geerts B, Ibrahim M, Liu X, Mateen B, Mathur P, McCradden M, Morgan L, Ordish J, Rogers C, Saria S, Ting D, Watkinson P, Weber W, Wheatstone P, McCulloch P. Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. BMJ 2022:e070904 View
  5. Beegle C, Hasani N, Maass-Moreno R, Saboury B, Siegel E. Artificial Intelligence and Positron Emission Tomography Imaging Workflow. PET Clinics 2022;17(1):31 View
  6. Sibbald M, Zwaan L, Yilmaz Y, Lal S. Incorporating artificial intelligence in medical diagnosis: A case for an invisible and (un)disruptive approach. Journal of Evaluation in Clinical Practice 2024;30(1):3 View
  7. Choudhury A, Asan O, Medow J. Effect of risk, expectancy, and trust on clinicians’ intent to use an artificial intelligence system -- Blood Utilization Calculator. Applied Ergonomics 2022;101:103708 View
  8. Vasey B, Nagendran M, Campbell B, Clifton D, Collins G, Denaxas S, Denniston A, Faes L, Geerts B, Ibrahim M, Liu X, Mateen B, Mathur P, McCradden M, Morgan L, Ordish J, Rogers C, Saria S, Ting D, Watkinson P, Weber W, Wheatstone P, McCulloch P, Lee A, Fraser A, Connell A, Vira A, Esteva A, Althouse A, Beam A, de Hond A, Boulesteix A, Bradlow A, Ercole A, Paez A, Tsanas A, Kirby B, Glocker B, Velardo C, Park C, Hehakaya C, Baber C, Paton C, Johner C, Kelly C, Vincent C, Yau C, McGenity C, Gatsonis C, Faivre-Finn C, Simon C, Sent D, Bzdok D, Treanor D, Wong D, Steiner D, Higgins D, Benson D, O’Regan D, Gunasekaran D, Danks D, Neri E, Kyrimi E, Schwendicke F, Magrabi F, Ives F, Rademakers F, Fowler G, Frau G, Hogg H, Marcus H, Chan H, Xiang H, McIntyre H, Harvey H, Kim H, Habli I, Fackler J, Shaw J, Higham J, Wohlgemut J, Chong J, Bibault J, Cohen J, Kers J, Morley J, Krois J, Monteiro J, Horovitz J, Fletcher J, Taylor J, Yoon J, Singh K, Moons K, Karpathakis K, Catchpole K, Hood K, Balaskas K, Kamnitsas K, Militello L, Wynants L, Oakden-Rayner L, Lovat L, Smits L, Hinske L, ElZarrad M, van Smeden M, Giavina-Bianchi M, Daley M, Sendak M, Sujan M, Rovers M, DeCamp M, Woodward M, Komorowski M, Marsden M, Mackintosh M, Abramoff M, de la Hoz M, Hambidge N, Daly N, Peek N, Redfern O, Ahmad O, Bossuyt P, Keane P, Ferreira P, Schnell-Inderst P, Mascagni P, Dasgupta P, Guan P, Barnett R, Kader R, Chopra R, Mann R, Sarkar R, Mäenpää S, Finlayson S, Vollam S, Vollmer S, Park S, Laher S, Joshi S, van der Meijden S, Shelmerdine S, Tan T, Stocker T, Giannini V, Madai V, Newcombe V, Ng W, Rogers W, Ogallo W, Park Y, Perkins Z. Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. Nature Medicine 2022;28(5):924 View
  9. Ciecierski-Holmes T, Singh R, Axt M, Brenner S, Barteit S. Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review. npj Digital Medicine 2022;5(1) View
  10. Choudhury A, Asan O. Impact of accountability, training, and human factors on the use of artificial intelligence in healthcare: Exploring the perceptions of healthcare practitioners in the US. Human Factors in Healthcare 2022;2:100021 View
  11. Wenderott K, Gambashidze N, Weigl M. Integration of Artificial Intelligence Into Sociotechnical Work Systems—Effects of Artificial Intelligence Solutions in Medical Imaging on Clinical Efficiency: Protocol for a Systematic Literature Review. JMIR Research Protocols 2022;11(12):e40485 View
  12. Wu C, Xu H, Bai D, Chen X, Gao J, Jiang X. Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis. BMJ Open 2023;13(1):e066322 View
  13. Tulk Jesso S, Kelliher A, Sanghavi H, Martin T, Henrickson Parker S. Inclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Review. Frontiers in Psychology 2022;13 View
  14. Choudhury A, Asan O. Impact of cognitive workload and situation awareness on clinicians’ willingness to use an artificial intelligence system in clinical practice. IISE Transactions on Healthcare Systems Engineering 2023;13(2):89 View
  15. Lee Y, Lee Y. Designing AI Agent’s Social Interaction Quality in AI-based Fitness Services as a Mediator. Archives of Design Research 2022;35(3):145 View
  16. Cabitza F, Campagner A, Natali C, Parimbelli E, Ronzio L, Cameli M. Painting the Black Box White: Experimental Findings from Applying XAI to an ECG Reading Setting. Machine Learning and Knowledge Extraction 2023;5(1):269 View
  17. Apostolopoulos I, Groumpos P. Fuzzy Cognitive Maps: Their Role in Explainable Artificial Intelligence. Applied Sciences 2023;13(6):3412 View
  18. Afshar M, Adelaine S, Resnik F, Mundt M, Long J, Leaf M, Ampian T, Wills G, Schnapp B, Chao M, Brown R, Joyce C, Sharma B, Dligach D, Burnside E, Mahoney J, Churpek M, Patterson B, Liao F. Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults. JMIR Medical Informatics 2023;11:e44977 View
  19. Liaw W, Ramos Silva Y, Soltero E, Krist A, Stotts A. An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study. JMIR AI 2023;2:e45032 View
  20. Wang B, Asan O, Mansouri M. Systems Approach in Telemedicine Adoption During and After COVID-19: Roles, Factors, and Challenges. IEEE Open Journal of Systems Engineering 2023;1:38 View
  21. Robinson R, Liday C, Lee S, Williams I, Wright M, An S, Nguyen E. Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study. JMIR AI 2023;2:e46487 View
  22. Hua D, Petrina N, Young N, Cho J, Poon S. Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review. Artificial Intelligence in Medicine 2024;147:102698 View
  23. Oh S, Kuang I, Jeong H, Song J, Ren B, Moon J, Park E, Kawachi I. Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study. Journal of Medical Internet Research 2023;25:e45041 View
  24. Scanzera A, Beversluis C, Potharazu A, Bai P, Leifer A, Cole E, Du D, Musick H, Chan R. Planning an artificial intelligence diabetic retinopathy screening program: a human-centered design approach. Frontiers in Medicine 2023;10 View
  25. Farič N, Hinder S, Williams R, Ramaesh R, Bernabeu M, van Beek E, Cresswell K. Early experiences of integrating an artificial intelligence-based diagnostic decision support system into radiology settings: a qualitative study. Journal of the American Medical Informatics Association 2023;31(1):24 View
  26. Wenderott K, Krups J, Luetkens J, Gambashidze N, Weigl M. Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists’ outcomes. European Journal of Radiology 2024;170:111252 View
  27. Cioffi G, Pinilla-Echeverri N, Sheth T, Sibbald M. Does artificial intelligence enhance physician interpretation of optical coherence tomography: insights from eye tracking. Frontiers in Cardiovascular Medicine 2023;10 View
  28. SOYSAL F. Enhancing Translation Studies with Artificial Intelligence (AI): Challenges, Opportunities, and Proposals. Karamanoğlu Mehmetbey Üniversitesi Uluslararası Filoloji ve Çeviribilim Dergisi 2023;5(2):177 View
  29. Wenderott K, Krups J, Luetkens J, Weigl M. Radiologists’ perspectives on the workflow integration of an artificial intelligence-based computer-aided detection system: A qualitative study. Applied Ergonomics 2024;117:104243 View
  30. Razakatiana M, Kolski C, Mandiau R, Mahatody T. Human-Agent Team Based on Decision Matrices: Application to Road Traffic Management in Participatory Simulation. Human-Centric Intelligent Systems 2024;4(2):241 View
  31. Lekadir K. A deep learning solution to detect left ventricular structural abnormalities with chest X-rays: towards trustworthy AI in cardiology. European Heart Journal 2024;45(22):2013 View
  32. Scott I, van der Vegt A, Lane P, McPhail S, Magrabi F. Achieving large-scale clinician adoption of AI-enabled decision support. BMJ Health & Care Informatics 2024;31(1):e100971 View

Books/Policy Documents

  1. Blandford A. Handbook of Human Computer Interaction. View
  2. Ebnali M, Zenati M, Dias R. Artificial Intelligence in Clinical Practice. View
  3. Asikullah F, Chakma P, Hossain M, Mahdi M. Utilizing AI and Smart Technology to Improve Sustainability in Entrepreneurship. View