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

Theme issue 2019: 20th Anniversary Issue (30)

Published on in Vol 21, No 11 (2019): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16323, first published .
The Last Mile: Where Artificial Intelligence Meets Reality

The Last Mile: Where Artificial Intelligence Meets Reality

The Last Mile: Where Artificial Intelligence Meets Reality

Authors of this article:

Enrico Coiera1 Author Orcid Image
Article Authors Cited by (49) Tweetations (193) Metrics

Journals

  1. Wang Y, Coiera E, Magrabi F. Can Unified Medical Language System–based semantic representation improve automated identification of patient safety incident reports by type and severity?. Journal of the American Medical Informatics Association 2020;27(10):1502 View
  2. Sorigue M, Cañamero E, Sancho J. Precision medicine in follicular lymphoma: Focus on predictive biomarkers. Hematological Oncology 2020;38(5):625 View
  3. Eysenbach G. Celebrating 20 Years of Open Access and Innovation at JMIR Publications. Journal of Medical Internet Research 2019;21(12):e17578 View
  4. Komorowski M. Clinical management of sepsis can be improved by artificial intelligence: yes. Intensive Care Medicine 2020;46(2):375 View
  5. Pedretti A, Mazzolari A, Gervasoni S, Vistoli G. Tree2C: A Flexible Tool for Enabling Model Deployment with Special Focus on Cheminformatics Applications. Applied Sciences 2020;10(21):7704 View
  6. Jucha P, Kliestik T. Use of artificial intelligence in last mile delivery. SHS Web of Conferences 2021;92:04011 View
  7. Lyell D, Coiera E, Chen J, Shah P, Magrabi F. How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices. BMJ Health & Care Informatics 2021;28(1):e100301 View
  8. Matthiesen S, Diederichsen S, Hansen M, Villumsen C, Lassen M, Jacobsen P, Risum N, Winkel B, Philbert B, Svendsen J, Andersen T. Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study. JMIR Human Factors 2021;8(4):e26964 View
  9. King Z, Farrington J, Utley M, Kung E, Elkhodair S, Harris S, Sekula R, Gillham J, Li K, Crowe S. Machine learning for real-time aggregated prediction of hospital admission for emergency patients. npj Digital Medicine 2022;5(1) View
  10. Emani S, Rui A, Rocha H, Rizvi R, Juaçaba S, Jackson G, Bates D. Physicians’ Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle–Income Countries. JMIR Cancer 2022;8(2):e31461 View
  11. Thieme A, Hanratty M, Lyons M, Palacios J, Marques R, Morrison C, Doherty G. Designing Human-centered AI for Mental Health: Developing Clinically Relevant Applications for Online CBT Treatment. ACM Transactions on Computer-Human Interaction 2023;30(2):1 View
  12. 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
  13. Ulloa M, Rothrock B, Ahmad F, Jacobs M. Invisible clinical labor driving the successful integration of AI in healthcare. Frontiers in Computer Science 2022;4 View
  14. Coiera E, Liu S. Evidence synthesis, digital scribes, and translational challenges for artificial intelligence in healthcare. Cell Reports Medicine 2022;3(12):100860 View
  15. Nilsen P, Reed J, Nair M, Savage C, Macrae C, Barlow J, Svedberg P, Larsson I, Lundgren L, Nygren J. Realizing the potential of artificial intelligence in healthcare: Learning from intervention, innovation, implementation and improvement sciences. Frontiers in Health Services 2022;2 View
  16. Werder K, Ramesh B, Zhang R. Establishing Data Provenance for Responsible Artificial Intelligence Systems. ACM Transactions on Management Information Systems 2022;13(2):1 View
  17. Bai E, Song S, Fraser H, Ranney M. A Graphical Toolkit for Longitudinal Dataset Maintenance and Predictive Model Training in Health Care. Applied Clinical Informatics 2022;13(01):056 View
  18. Hong J, Eclov N, Stephens S, Mowery Y, Palta M. Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study. BMC Bioinformatics 2022;23(S12) View
  19. Walker S, Badke C, Carroll M, Honegger K, Fawcett A, Weese-Mayer D, Sanchez-Pinto L. Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children. Pediatric Research 2023;93(2):396 View
  20. Salwei M, Carayon P. A Sociotechnical Systems Framework for the Application of Artificial Intelligence in Health Care Delivery. Journal of Cognitive Engineering and Decision Making 2022;16(4):194 View
  21. Naemi A, Schmidt T, Mansourvar M, Naghavi-Behzad M, Ebrahimi A, Wiil U. Machine learning techniques for mortality prediction in emergency departments: a systematic review. BMJ Open 2021;11(11):e052663 View
  22. Reddy S, Rogers W, Makinen V, Coiera E, Brown P, Wenzel M, Weicken E, Ansari S, Mathur P, Casey A, Kelly B. Evaluation framework to guide implementation of AI systems into healthcare settings. BMJ Health & Care Informatics 2021;28(1):e100444 View
  23. Roig P, Alcaraz S, Gilly K, Bernad C, Juiz C. Formal Algebraic Model of an Edge Data Center with a Redundant Ring Topology. Network 2023;3(1):142 View
  24. van der Meijden S, de Hond A, Thoral P, Steyerberg E, Kant I, Cinà G, Arbous M. Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study. JMIR Human Factors 2023;10:e39114 View
  25. Rees N, Holding K, Sujan M. Information governance as a socio-technical process in the development of trustworthy healthcare AI. Frontiers in Computer Science 2023;5 View
  26. Zając H, Li D, Dai X, Carlsen J, Kensing F, Andersen T. Clinician-Facing AI in the Wild: Taking Stock of the Sociotechnical Challenges and Opportunities for HCI. ACM Transactions on Computer-Human Interaction 2023;30(2):1 View
  27. Cummings B, Blackmer J, Motyka J, Farzaneh N, Cao L, Bisco E, Glassbrook J, Roebuck M, Gillies C, Admon A, Medlin R, Singh K, Sjoding M, Ward K, Ansari S. External Validation and Comparison of a General Ward Deterioration Index Between Diversely Different Health Systems. Critical Care Medicine 2023;51(6):775 View
  28. Gyldenkærne C, Hansen J, Hertzum M, Mønsted T. Innovation tactics for implementing an ML application in healthcare: A long and winding road. International Journal of Human-Computer Studies 2024;181:103162 View
  29. Campagner A, Famiglini L, Carobene A, Cabitza F. Everything is varied: The surprising impact of instantial variation on ML reliability. Applied Soft Computing 2023;146:110644 View
  30. Gonzales J. Implications of AI innovation on economic growth: a panel data study. Journal of Economic Structures 2023;12(1) View
  31. Andersen T, Nunes F, Wilcox L, Coiera E, Rogers Y. Introduction to the Special Issue on Human-Centred AI in Healthcare: Challenges Appearing in the Wild. ACM Transactions on Computer-Human Interaction 2023;30(2):1 View
  32. Kannelønning M. Contesting futures of Artificial Intelligence (AI) in healthcare: formal expectations meet informal anticipations. Technology Analysis & Strategic Management 2023:1 View
  33. Susanto A, Lyell D, Widyantoro B, Berkovsky S, Magrabi F. Effects of machine learning-based clinical decision support systems on decision-making, care delivery, and patient outcomes: a scoping review. Journal of the American Medical Informatics Association 2023;30(12):2050 View
  34. Nilsen P, Svedberg P, Neher M, Nair M, Larsson I, Petersson L, Nygren J. A Framework to Guide Implementation of AI in Health Care: Protocol for a Cocreation Research Project. JMIR Research Protocols 2023;12:e50216 View
  35. Cresswell K, Rigby M, Magrabi F, Scott P, Brender J, Craven C, Wong Z, Kukhareva P, Ammenwerth E, Georgiou A, Medlock S, De Keizer N, Nykänen P, Prgomet M, Williams R. The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision. Health Policy 2023;136:104889 View
  36. Kannelønning M. Navigating uncertainties of introducing artificial intelligence (AI) in healthcare: The role of a Norwegian network of professionals. Technology in Society 2024;76:102432 View
  37. Sujan M. Integrating digital health technologies into complex clinical systems. BMJ Health & Care Informatics 2023;30(1):e100885 View
  38. Macrae C. Managing risk and resilience in autonomous and intelligent systems: Exploring safety in the development, deployment, and use of artificial intelligence in healthcare. Risk Analysis 2024 View
  39. McLennan S, Fiske A, Celi L. Building a house without foundations? A 24-country qualitative interview study on artificial intelligence in intensive care medicine. BMJ Health & Care Informatics 2024;31(1):e101052 View
  40. Ooi K. Using Artificial Intelligence in Patient Care—Some Considerations for Doctors and Medical Regulators. Asian Bioethics Review 2024;16(3):483 View

Books/Policy Documents

  1. Korngiebel D, Solomonides A, Goodman K. Intelligent Systems in Medicine and Health. View
  2. Daneshvar H, Boursalie O, Samavi R, Doyle T, Duncan L, Pires P, Sassi R. Artificial Intelligence for Medicine. View
  3. Cabitza F, Campagner A. Big Data Analysis and Artificial Intelligence for Medical Sciences. View