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 2020 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 pandemic: The role of voice technology (Preprint). Journal of Medical Internet Research 2020 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 2021:097226292098839 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

Books/Policy Documents

  1. Ulapane N, Wickramasinghe N. Optimizing Health Monitoring Systems With Wireless Technology. View