Published on in Vol 21 , No 7 (2019) :July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13659, first published .
Artificial Intelligence and the Implementation Challenge

Artificial Intelligence and the Implementation Challenge

Artificial Intelligence and the Implementation Challenge

Journals

  1. Goulooze S, Zwep L, Vogt J, Krekels E, Hankemeier T, Anker J, Knibbe C. Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap. Clinical Pharmacology & Therapeutics 2020;107(4):786 View
  2. Lee T, Shah N, Haack A, Baxter S. Clinical Implementation of Predictive Models Embedded within Electronic Health Record Systems: A Systematic Review. Informatics 2020;7(3):25 View
  3. Powell J. Trust Me, I’m a Chatbot: How Artificial Intelligence in Health Care Fails the Turing Test. Journal of Medical Internet Research 2019;21(10):e16222 View
  4. Adly A, Adly A, Adly M. Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review. Journal of Medical Internet Research 2020;22(8):e19104 View
  5. Xiang Y, Zhao L, Liu Z, Wu X, Chen J, Long E, Lin D, Zhu Y, Chen C, Lin Z, Lin H. Implementation of artificial intelligence in medicine: Status analysis and development suggestions. Artificial Intelligence in Medicine 2020;102:101780 View
  6. Alami H, Lehoux P, Auclair Y, de Guise M, Gagnon M, Shaw J, Roy D, Fleet R, Ag Ahmed M, Fortin J. Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity. Journal of Medical Internet Research 2020;22(7):e17707 View
  7. Javaid M, Haleem A, Khan I, Vaishya R, Vaish A. Extending capabilities of artificial intelligence for decision-making and healthcare education. Apollo Medicine 2020;17(1):53 View
  8. Abd-Alrazaq A, Alajlani M, Alhuwail D, Schneider J, Al-Kuwari S, Shah Z, Hamdi M, Househ M. Artificial Intelligence in the Fight Against COVID-19: Scoping Review. Journal of Medical Internet Research 2020;22(12):e20756 View
  9. . A Path for Translation of Machine Learning Products into Healthcare Delivery. EMJ Innovations 2020 View
  10. Assadullah M. Barriers to Artificial Intelligence Adoption in Healthcare Management: A Systematic Review. SSRN Electronic Journal 2019 View
  11. Sendak M, Ratliff W, Sarro D, Alderton E, Futoma J, Gao M, Nichols M, Revoir M, Yashar F, Miller C, Kester K, Sandhu S, Corey K, Brajer N, Tan C, Lin A, Brown T, Engelbosch S, Anstrom K, Elish M, Heller K, Donohoe R, Theiling J, Poon E, Balu S, Bedoya A, O'Brien C. Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study. JMIR Medical Informatics 2020;8(7):e15182 View
  12. Morley J, Floridi L, Goldacre B. The poor performance of apps assessing skin cancer risk. BMJ 2020:m428 View
  13. Bukowski M, Farkas R, Beyan O, Moll L, Hahn H, Kiessling F, Schmitz-Rode T. Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?. European Radiology 2020;30(10):5510 View
  14. Sisk B, Antes A, Burrous S, DuBois J. Parental Attitudes toward Artificial Intelligence-Driven Precision Medicine Technologies in Pediatric Healthcare. Children 2020;7(9):145 View
  15. Baxter S, Bass J, Sitapati A. Barriers to Implementing an Artificial Intelligence Model for Unplanned Readmissions. ACI Open 2020;04(02):e108 View
  16. Chou M, Illa-Bochaca I, Minxi B, Darvishian F, Johannet P, Moran U, Shapiro R, Berman R, Osman I, Jour G, Zhong H. Optimization of an automated tumor-infiltrating lymphocyte algorithm for improved prognostication in primary melanoma. Modern Pathology 2021;34(3):562 View
  17. Shaw J, Sethi N, Block B. Five things every clinician should know about AI ethics in intensive care. Intensive Care Medicine 2021;47(2):157 View
  18. Baxter S, Saseendrakumar B, Paul P, Kim J, Bonomi L, Kuo T, Loperena R, Ratsimbazafy F, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Mayo K, Mockrin S, Schully S, Ramirez A, Ohno-Machado L. Predictive Analytics for Glaucoma Using Data From the All of Us Research Program. American Journal of Ophthalmology 2021;227:74 View
  19. Goel P, Jain P, Pasman H, Pistikopoulos E, Datta A. Integration of data analytics with cloud services for safer process systems, application examples and implementation challenges. Journal of Loss Prevention in the Process Industries 2020;68:104316 View
  20. Begley K, Begley C, Smith V. Shared decision‐making and maternity care in the deep learning age: Acknowledging and overcoming inherited defeaters. Journal of Evaluation in Clinical Practice 2021;27(3):497 View
  21. Alexander J, Romito B, Çobanoğlu M. The present and future role of artificial intelligence and machine learning in anesthesiology. International Anesthesiology Clinics 2020;Publish Ahead of Print View
  22. Ilan Y. Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes. Frontiers in Digital Health 2020;2 View
  23. Jadczyk T, Wojakowski W, Tendera M, Henry T, Egnaczyk G, Shreenivas S. Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology. Journal of Medical Internet Research 2021;23(5):e22959 View
  24. Tong H, Quiroz J, Kocaballi A, Fat S, Dao K, Gehringer H, Chow C, Laranjo L. Personalized mobile technologies for lifestyle behavior change: A systematic review, meta-analysis, and meta-regression. Preventive Medicine 2021;148:106532 View
  25. Maassen O, Fritsch S, Palm J, Deffge S, Kunze J, Marx G, Riedel M, Schuppert A, Bickenbach J. Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey. Journal of Medical Internet Research 2021;23(3):e26646 View
  26. Yin J, Ngiam K, Teo H. Role of Artificial Intelligence Applications in Real-Life Clinical Practice: Systematic Review. Journal of Medical Internet Research 2021;23(4):e25759 View
  27. Bhatt S, Cohon A, Rose J, Majerczyk N, Cozzi B, Crenshaw D, Myers G. Interpretable Machine Learning Models for Clinical Decision-Making in a High-Need, Value-Based Primary Care Setting. NEJM Catalyst 2021;2(4) View
  28. Al Badi F, Alhosani K, Jabeen F, Stachowicz-Stanusch A, Shehzad N, AMANN W. Challenges of AI Adoption in the UAE Healthcare. Vision: The Journal of Business Perspective 2022;26(2):193 View
  29. Bates D, Levine D, Syrowatka A, Kuznetsova M, Craig K, Rui A, Jackson G, Rhee K. The potential of artificial intelligence to improve patient safety: a scoping review. npj Digital Medicine 2021;4(1) View
  30. Korinek A, Stiglitz J. Covid-19 driven advances in automation and artificial intelligence risk exacerbating economic inequality. BMJ 2021:n367 View
  31. Shung D, Sung J. Challenges of developing artificial intelligence‐assisted tools for clinical medicine. Journal of Gastroenterology and Hepatology 2021;36(2):295 View
  32. Kordzadeh N, Ghasemaghaei M. Algorithmic bias: review, synthesis, and future research directions. European Journal of Information Systems 2022;31(3):388 View
  33. Ahn J, Connell A, Simonetto D, Hughes C, Shah V. Application of Artificial Intelligence for the Diagnosis and Treatment of Liver Diseases. Hepatology 2021;73(6):2546 View
  34. Antes A, Burrous S, Sisk B, Schuelke M, Keune J, DuBois J. Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey. BMC Medical Informatics and Decision Making 2021;21(1) View
  35. Alzubaidi M, Zubaydi H, Bin-Salem A, Abd-Alrazaq A, Ahmed A, Househ M. Role of deep learning in early detection of COVID-19: Scoping review. Computer Methods and Programs in Biomedicine Update 2021;1:100025 View
  36. Baxter S, Lee A. Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice. Current Opinion in Ophthalmology 2021;32(5):431 View
  37. d'Elia A, Gabbay M, Rodgers S, Kierans C, Jones E, Durrani I, Thomas A, Frith L. Artificial intelligence and health inequities in primary care: a systematic scoping review and framework. Family Medicine and Community Health 2022;10(Suppl 1):e001670 View
  38. Torrent-Sellens J, Jiménez-Zarco A, Saigí-Rubió F. Do People Trust in Robot-Assisted Surgery? Evidence from Europe. International Journal of Environmental Research and Public Health 2021;18(23):12519 View
  39. Saini F, Sharma T, Madan S. A Comparative Analysis of Expert Opinions on Artificial Intelligence: Evolution, Applications, and Its Future. Advanced Journal of Graduate Research 2021;11(1):10 View
  40. Pumplun L, Fecho M, Wahl N, Peters F, Buxmann P. Adoption of Machine Learning Systems for Medical Diagnostics in Clinics: Qualitative Interview Study. Journal of Medical Internet Research 2021;23(10):e29301 View
  41. Åström J, Reim W, Parida V. Value creation and value capture for AI business model innovation: a three-phase process framework. Review of Managerial Science 2022;16(7):2111 View
  42. Khanijahani A, Iezadi S, Dudley S, Goettler M, Kroetsch P, Wise J. Organizational, professional, and patient characteristics associated with artificial intelligence adoption in healthcare: A systematic review. Health Policy and Technology 2022;11(1):100602 View
  43. Wang C, Zhang W, Wang S. An asymptotically optimal public parking lot location algorithm based on intuitive reasoning. Intelligent and Converged Networks 2022;3(3):260 View
  44. Bin K, Melo A, da Rocha J, de Almeida R, Cobello Junior V, Maia F, de Faria E, Pereira A, Battistella L, Ono S. The Impact of Artificial Intelligence on Waiting Time for Medical Care in an Urgent Care Service for COVID-19: Single-Center Prospective Study. JMIR Formative Research 2022;6(2):e29012 View
  45. Chen S, Novoa R. Artificial intelligence for dermatopathology: Current trends and the road ahead. Seminars in Diagnostic Pathology 2022;39(4):298 View
  46. Gama F, Tyskbo D, Nygren J, Barlow J, Reed J, Svedberg P. Implementation Frameworks for Artificial Intelligence Translation Into Health Care Practice: Scoping Review. Journal of Medical Internet Research 2022;24(1):e32215 View
  47. Scott I, Carter S, Coiera E. Exploring stakeholder attitudes towards AI in clinical practice. BMJ Health & Care Informatics 2021;28(1):e100450 View
  48. Nilsen P, Svedberg P, Nygren J, Frideros M, Johansson J, Schueller S. Accelerating the impact of artificial intelligence in mental healthcare through implementation science. Implementation Research and Practice 2022;3:263348952211120 View
  49. Cornelissen L, Egher C, van Beek V, Williamson L, Hommes D. The Drivers of Acceptance of Artificial Intelligence–Powered Care Pathways Among Medical Professionals: Web-Based Survey Study. JMIR Formative Research 2022;6(6):e33368 View
  50. Kyung N, Kwon H. Rationally trust, but emotionally? The roles of cognitive and affective trust in laypeople's acceptance of AI for preventive care operations. Production and Operations Management 2022 View
  51. Etchebehere E, Andrade R, Camacho M, Lima M, Brink A, Cerci J, Nadel H, Bal C, Rangarajan V, Pfluger T, Kagna O, Alonso O, Begum F, Mir K, Magboo V, Menezes L, Paez D, Pascual T. Validation of Convolutional Neural Networks for Fast Determination of Whole-Body Metabolic Tumor Burden in Pediatric Lymphoma. Journal of Nuclear Medicine Technology 2022;50(3):256 View
  52. King H, Wright J, Treanor D, Williams B, Randell R. What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation. Journal of Medical Internet Research 2023;25:e38039 View
  53. Lu S, Swisher C, Chung C, Jaffray D, Sidey-Gibbons C. On the importance of interpretable machine learning predictions to inform clinical decision making in oncology. Frontiers in Oncology 2023;13 View
  54. 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
  55. Tricco A, Hezam A, Parker A, Nincic V, Harris C, Fennelly O, Thomas S, Ghassemi M, McGowan J, Paprica P, Straus S. Implemented machine learning tools to inform decision-making for patient care in hospital settings: a scoping review. BMJ Open 2023;13(2):e065845 View
  56. s K. Artificial Intelligence on Medical Fields. Data Analytics and Artificial Intelligence 2023;3(2):113 View
  57. Nickel P. Trust in medical artificial intelligence: a discretionary account. Ethics and Information Technology 2022;24(1) View
  58. Hehakaya C, Sharma A, van der Voort Van Zijp J, Grobbee D, Verkooijen H, Izaguirre E, Moors E. Implementation of Magnetic Resonance Imaging-Guided Radiation Therapy in Routine Care: Opportunities and Challenges in the United States. Advances in Radiation Oncology 2022;7(5):100953 View
  59. Joshi M, Mecklai K, Rozenblum R, Samal L. Implementation approaches and barriers for rule-based and machine learning-based sepsis risk prediction tools: a qualitative study. JAMIA Open 2022;5(2) View
  60. Jaiswal A, Yigzaw K, Ozturk P. F-CBR: An Architecture for Federated Case-Based Reasoning. IEEE Access 2022;10:75458 View
  61. Weinert L, Klass M, Schneider G, Heinze O. Exploring Stakeholder Requirements to Enable the Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Protocol for a Multistep Mixed Methods Study. JMIR Research Protocols 2022;11(12):e42208 View
  62. Shaw J, Donia J. The Sociotechnical Ethics of Digital Health: A Critique and Extension of Approaches From Bioethics. Frontiers in Digital Health 2021;3 View
  63. Kaul R, Ossai C, Forkan A, Jayaraman P, Zelcer J, Vaughan S, Wickramasinghe N. The role of AI for developing digital twins in healthcare: The case of cancer care. WIREs Data Mining and Knowledge Discovery 2023;13(1) View
  64. 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
  65. Abbasgholizadeh Rahimi S, Légaré F, Sharma G, Archambault P, Zomahoun H, Chandavong S, Rheault N, T Wong S, Langlois L, Couturier Y, Salmeron J, Gagnon M, Légaré J. Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal. Journal of Medical Internet Research 2021;23(9):e29839 View
  66. Penrice D, Rattan P, Simonetto D. Artificial Intelligence and the Future of Gastroenterology and Hepatology. Gastro Hep Advances 2022;1(4):581 View
  67. Shaw J. Emerging Paradigms for Ethical Review of Research Using Artificial Intelligence. The American Journal of Bioethics 2022;22(5):42 View
  68. Costa-Climent R, Haftor D, Staniewski M. Using machine learning to create and capture value in the business models of small and medium-sized enterprises. International Journal of Information Management 2023:102637 View
  69. Siala H, Wang Y. SHIFTing artificial intelligence to be responsible in healthcare: A systematic review. Social Science & Medicine 2022;296:114782 View
  70. Брызгалина Е. DIGITAL BIOETHICS AS DIGITAL HEALTH ETHICS. ΠΡΑΞΗMΑ. Journal of Visual Semiotics 2023;(1(35)):9 View
  71. Bélisle-Pipon J, Couture V, Roy M, Ganache I, Goetghebeur M, Cohen I. What Makes Artificial Intelligence Exceptional in Health Technology Assessment?. Frontiers in Artificial Intelligence 2021;4 View
  72. Nedadur R, Wang B, Tsang W. Artificial intelligence for the echocardiographic assessment of valvular heart disease. Heart 2022;108(20):1592 View
  73. Petersson L, Larsson I, Nygren J, Nilsen P, Neher M, Reed J, Tyskbo D, Svedberg P. Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden. BMC Health Services Research 2022;22(1) View
  74. Weinert L, Klass M, Schneider G, Heinze O. Exploring Stakeholder Requirements to Enable Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Results of a Multistep Mixed Methods Study. JMIR Formative Research 2023;7:e43958 View
  75. Costa-Climent R. The Role of Machine Learning in Creating and Capturing Value. International Journal of Software Science and Computational Intelligence 2022;14(1):1 View
  76. Wang Y, Zhang N, Zhao X. Understanding the Determinants in the Different Government AI Adoption Stages: Evidence of Local Government Chatbots in China. Social Science Computer Review 2022;40(2):534 View
  77. Li R, Li H. Artificial intelligence will be a milestone in medical imaging development. Radiology of Infectious Diseases 2022;9(3):96 View
  78. Shan Y, Ji M, Xie W, Lam K, Chow C. Public Trust in Artificial Intelligence Applications in Mental Health Care: Topic Modeling Analysis. JMIR Human Factors 2022;9(4):e38799 View
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  80. Kossowsky H, Nisky I. Predicting the Timing of Camera Movements From the Kinematics of Instruments in Robotic-Assisted Surgery Using Artificial Neural Networks. IEEE Transactions on Medical Robotics and Bionics 2022;4(2):391 View
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  82. Joshi S, Sharma M, Das R, Rosak-Szyrocka J, Żywiołek J, Muduli K, Prasad M. Modeling Conceptual Framework for Implementing Barriers of AI in Public Healthcare for Improving Operational Excellence: Experiences from Developing Countries. Sustainability 2022;14(18):11698 View
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Books/Policy Documents

  1. Ulapane N, Wickramasinghe N. Optimizing Health Monitoring Systems With Wireless Technology. View
  2. Samori I, Palmer X, Potter L, Karahan S. Intelligent Systems and Applications. View
  3. Mohamad I, Hughes L, Dwivedi Y, Alalwan A. The Role of Digital Technologies in Shaping the Post-Pandemic World. View
  4. Ulapane N, Wickramasinghe N. Digital Disruption in Health Care. View
  5. Doguc O. Handbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World. View