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

Digital Health Reviews (1186) Artificial Intelligence (1198) Decision Support for Health Professionals (1137)

Published on in Vol 24, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36823, first published .
Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks

Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks

Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks

Authors of this article:

Norah L Crossnohere1, 2 Author Orcid Image ;   Mohamed Elsaid1 Author Orcid Image ;   Jonathan Paskett1 Author Orcid Image ;   Seuli Bose-Brill2 Author Orcid Image ;   John F P Bridges1 Author Orcid Image
Article Authors Cited by (40) Tweetations (24) Metrics

Journals

  1. KELEŞ H. TIPTA YAPAY ZEKA UYGULAMALARI. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi 2022;24(3):604 View
  2. Kharb S, Joshi A. Multi-omics and machine learning for the prevention and management of female reproductive health. Frontiers in Endocrinology 2023;14 View
  3. Crossnohere N, Childerhose J, Bose-Brill S. Increasing the Patient-Centeredness of Predictive Analytics Tools. The Patient - Patient-Centered Outcomes Research 2022;15(6):615 View
  4. Zou K, Li J. Enhanced Patient-Centricity: How the Biopharmaceutical Industry Is Optimizing Patient Care through AI/ML/DL. Healthcare 2022;10(10):1997 View
  5. 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
  6. Zulqarnain F, Rhoads S, Syed S. Machine and deep learning in inflammatory bowel disease. Current Opinion in Gastroenterology 2023;39(4):294 View
  7. Kavian J, Wilkey H, Patel P, Boyd C. Harvesting the Power of Artificial Intelligence for Surgery: Uses, Implications, and Ethical Considerations. The American Surgeon™ 2023;89(12):5102 View
  8. Titov O, Bykanov A, Pitskhelauri D. Neurosurgical skills analysis by machine learning models: systematic review. Neurosurgical Review 2023;46(1) View
  9. van der Vegt A, Scott I, Dermawan K, Schnetler R, Kalke V, Lane P. Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework. Journal of the American Medical Informatics Association 2023;30(9):1503 View
  10. Klement W, El Emam K. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation. Journal of Medical Internet Research 2023;25:e48763 View
  11. Price R. From the Editor. Microscopy Today 2023;31(6):7 View
  12. Makridis C, Boese A, Fricks R, Workman D, Klote M, Mueller J, Hildebrandt I, Kim M, Alterovitz G. Informing the ethical review of human subjects research utilizing artificial intelligence. Frontiers in Computer Science 2023;5 View
  13. SAI CHARAN L. REVIEW ON THE POTENTIAL FOR ARTIFICIAL INTELLIGENCE TO REVOLUTIONIZE HEALTHCARE DIAGNOSTICS. SALT Journal of Scientific Research in Healthcare 2023:23 View
  14. van der Vegt A, Campbell V, Mitchell I, Malycha J, Simpson J, Flenady T, Flabouris A, Lane P, Mehta N, Kalke V, Decoyna J, Es’haghi N, Liu C, Scott I. Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain. Journal of the American Medical Informatics Association 2024;31(2):509 View
  15. Kaneko M, Magoulianitis V, Ramacciotti L, Raman A, Paralkar D, Chen A, Chu T, Yang Y, Xue J, Yang J, Liu J, Jadvar D, Gill K, Cacciamani G, Nikias C, Duddalwar V, Jay Kuo C, Gill I, Abreu A. The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging. Urologic Clinics of North America 2024;51(1):1 View
  16. Kelkar A, Hantel A, Koranteng E, Cutler C, Hammer M, Abel G. Digital Health to Patient-Facing Artificial Intelligence: Ethical Implications and Threats to Dignity for Patients With Cancer. JCO Oncology Practice 2024;20(3):314 View
  17. Sumner J, Lim H, Chong L, Bundele A, Mukhopadhyay A, Kayambu G. Artificial intelligence in physical rehabilitation: A systematic review. Artificial Intelligence in Medicine 2023;146:102693 View
  18. Alowais S, Alghamdi S, Alsuhebany N, Alqahtani T, Alshaya A, Almohareb S, Aldairem A, Alrashed M, Bin Saleh K, Badreldin H, Al Yami M, Al Harbi S, Albekairy A. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Medical Education 2023;23(1) View
  19. Rodriguez H, Rust B, Hansen P, Maffulli N, Gupta M, Potty A, Gupta A. Artificial Intelligence and Machine Learning in Rotator Cuff Tears. Sports Medicine and Arthroscopy Review 2023;31(3):67 View
  20. Rahrooh A, Garlid A, Bartlett K, Coons W, Petousis P, Hsu W, Bui A. Towards a framework for interoperability and reproducibility of predictive models. Journal of Biomedical Informatics 2024;149:104551 View
  21. van Velzen M, de Graaf-Waar H, Ubert T, van der Willigen R, Muilwijk L, Schmitt M, Scheper M, van Meeteren N. 21st century (clinical) decision support in nursing and allied healthcare. Developing a learning health system: a reasoned design of a theoretical framework. BMC Medical Informatics and Decision Making 2023;23(1) View
  22. Miao J, Thongprayoon C, Suppadungsuk S, Garcia Valencia O, Qureshi F, Cheungpasitporn W. Innovating Personalized Nephrology Care: Exploring the Potential Utilization of ChatGPT. Journal of Personalized Medicine 2023;13(12):1681 View
  23. He X, Zheng X, Ding H. Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review. Journal of Medical Internet Research 2023;25:e50342 View
  24. Rahman W, Abdelkader A, Lee S, Yang P, Islam M, Adnan T, Hasan M, Wagner E, Park S, Dorsey E, Schwartz C, Jaffe K, Hoque E. A User-Centered Framework to Empower People with Parkinson's Disease. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2023;7(4):1 View
  25. Thangaraju P, Sudha TY S, Velmurugan H, Thangaraju E, Chirumamilla K, Chakrabarti T, Chakrabarti P. A Registry-based Audit of a Current Situation of Clinical Research in COVID-19 Using Artificial Intelligence Techniques: A Systematic Review. Coronaviruses 2023;4(4) View
  26. Tiwade Y, Bankar N, Mishra V, Sajjanar A. Review of the potential benefits and challenges of artificial intelligence in clinical laboratory. Journal of Cellular Biotechnology 2024;10(1):17 View
  27. Hobensack M, von Gerich H, Vyas P, Withall J, Peltonen L, Block L, Davies S, Chan R, Van Bulck L, Cho H, Paquin R, Mitchell J, Topaz M, Song J. A rapid review on current and potential uses of large language models in nursing. International Journal of Nursing Studies 2024;154:104753 View
  28. Shen O, Pratap J, Li X, Chen N, Bhashyam A. How Does ChatGPT Use Source Information Compared With Google? A Text Network Analysis of Online Health Information. Clinical Orthopaedics & Related Research 2024;482(4):578 View
  29. Rosselló-Jiménez D, Docampo S, Collado Y, Cuadra-Llopart L, Riba F, Llonch-Masriera M. Geriatrics and artificial intelligence in Spain (Ger-IA project): talking to ChatGPT, a nationwide survey. European Geriatric Medicine 2024 View
  30. Lee S. Development of a chest X-ray machine learning convolutional neural network model on a budget and using artificial intelligence explainability techniques to analyze patterns of machine learning inference. JAMIA Open 2024;7(2) View
  31. Hartmann L, Langhans D, Eggarter V, Freisenich T, Hillenmayer A, König S, Vounotrypidis E, Wolf A, Wertheimer C. Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data. Translational Vision Science & Technology 2024;13(5):7 View
  32. Soukup T, Dean Franklin B. Quality, safety and artificial intelligence. BMJ Quality & Safety 2024;33(6):406 View
  33. Obradovich N, Khalsa S, Khan W, Suh J, Perlis R, Ajilore O, Paulus M. Opportunities and risks of large language models in psychiatry. NPP—Digital Psychiatry and Neuroscience 2024;2(1) View
  34. Buetow S, Lovatt J. From insight to innovation: Harnessing artificial intelligence for dynamic literature reviews. The Journal of Academic Librarianship 2024;50(4):102901 View
  35. Shlobin N, Ward M, Shah H, Brown E, Sciubba D, Langer D, D'Amico R. Ethical Incorporation of Artificial Intelligence into Neurosurgery: A Generative Pretrained Transformer Chatbot-Based, Human-Modified Approach. World Neurosurgery 2024;187:e769 View
  36. 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
  37. Aslan S. ARTIFICIAL INTELLIGENCE IN CLINICAL APPLICATIONS FOR INFECTIOUS DISEASES: DIAGNOSIS, TREATMENT AND IMMUNIZATION. Experimental and Applied Medical Science 2024 View

Books/Policy Documents

  1. Sonawane U, Komorowski M. Beyond Quantity. View
  2. Baum S, Manikas K. Pervasive Computing Technologies for Healthcare. View