A scoping review of educational programmes on artificial intelligence (AI) available to medical imaging staff

被引:6
|
作者
Doherty, G. [1 ,4 ]
Mclaughlin, L. [1 ]
Hughes, C. [1 ]
Mcconnell, J. [2 ]
Bond, R. [3 ]
Mcfadden, S. [1 ]
机构
[1] Ulster Univ, Fac Life & Hlth Sci, Sch Hlth Sci, Shore Rd, Newtownabbey, North Ireland
[2] Leeds Teaching Hosp NHS Trust, Leeds, England
[3] Ulster Univ, Fac Comp Engn & Built Environm, Sch Comp, Shore Rd, Newtownabbey, North Ireland
[4] Ulster Univ, Sch Hlth Sci, Room BC-04-121, York Rd, Belfast BT15 5ED, North Ireland
关键词
Artificial intelligence; Education; Medical imaging; Radiology; Radiography; MODEL;
D O I
10.1016/j.radi.2023.12.019
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Introduction: Medical imaging is arguably the most technologically advanced field in healthcare, encompassing a range of technologies which continually evolve as computing power and human knowledge expand. Artificial Intelligence (AI) is the next frontier which medical imaging is pioneering. The rapid development and implementation of AI has the potential to revolutionise healthcare, however, to do so, staff must be competent and confident in its application, hence AI readiness is an important precursor to AI adoption. Research to ascertain the best way to deliver this AI-enabled healthcare training is in its infancy. The aim of this scoping review is to compare existing studies which investigate and evaluate the efficacy of AI educational interventions for medical imaging staff. Methods: Following the creation of a search strategy and keyword searches, screening was conducted to determine study eligibility. This consisted of a title and abstract scan, then subsequently a full-text review. Articles were included if they were empirical studies wherein an educational intervention on AI for medical imaging staff was created, delivered, and evaluated. Results: Of the initial 1309 records returned, n = 5 (similar to 0.4 %) of studies met the eligibility criteria of the review. The curricula and delivery in each of the five studies shared similar aims and a 'flipped classroom' delivery was the most utilised method. However, the depth of content covered in the curricula of each varied and measured outcomes differed greatly. Conclusion: The findings of this review will provide insights into the evaluation of existing AI educational interventions, which will be valuable when planning AI education for healthcare staff. Implications for practice: This review highlights the need for standardised and comprehensive AI training programs for imaging staff.
引用
收藏
页码:474 / 482
页数:9
相关论文
共 50 条
  • [21] AI in Medical Imaging: Current and Future Status-Artificial Intelligence or Augmented Imaging?
    Kohli, Anirudh
    INDIAN JOURNAL OF RADIOLOGY AND IMAGING, 2021, 31 (03): : 525 - 526
  • [22] Will artificial intelligence (AI) replace cytopathologists: a scoping review of current applications and evidence of AI in urine cytology
    Li, Jingqiu
    Chong, Tsung Wen
    Fong, Khi Yung
    Han, Benjamin Lim Jia
    Tan, Si Ying
    Mui, Joanne Tan San
    Khor, Li Yan
    Somoni, Bhaskar Kumar
    Herrmann, Thomas R. W.
    Gauhar, Vineet
    Li, Valerie Gan Huei
    Sam, Christopher Cheng Wai
    Lim, Ee Jean
    WORLD JOURNAL OF UROLOGY, 2025, 43 (01)
  • [23] Artificial intelligence (AI) in diagnostic imaging
    Braunschweig, Rainer
    Kildal, Daniela
    Janka, Rolf
    ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2024, 196 (07): : 664 - 670
  • [24] Ethical Artificial Intelligence (AI) in Educational Leadership: Literature Review and Bibliometric Analysis
    Polat, Murat
    Karatas, Ibrahim Hakan
    Varol, Nurgun
    LEADERSHIP AND POLICY IN SCHOOLS, 2025, 24 (01) : 46 - 76
  • [25] A literature review of artificial intelligence (AI) for medical image segmentation: from AI and explainable AI to trustworthy AI
    Teng, Zixuan
    Li, Lan
    Xin, Ziqing
    Xiang, Dehui
    Huang, Jiang
    Zhou, Hailing
    Shi, Fei
    Zhu, Weifang
    Cai, Jing
    Peng, Tao
    Chen, Xinjian
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2024, 14 (12) : 9620 - 9652
  • [26] Perceptions and attitudes of health science students relating to artificial intelligence (AI): A scoping review
    Derakhshanian, Shokoufeh
    Wood, Lucy
    Arruzza, Elio
    HEALTH SCIENCE REPORTS, 2024, 7 (08)
  • [27] Artificial Intelligence in Resuscitation: A Scoping Review
    Viderman, Dmitriy
    Abdildin, Yerkin G. G.
    Batkuldinova, Kamila
    Badenes, Rafael
    Bilotta, Federico
    JOURNAL OF CLINICAL MEDICINE, 2023, 12 (06)
  • [28] Artificial intelligence in dentistry - A scoping review
    Vashisht, Ruchi
    Sharma, Aaina
    Kiran, Tanvi
    Jolly, Satnam Singh
    Brar, Prabhleen Kaur
    Puri, Jay Veer
    JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY MEDICINE AND PATHOLOGY, 2024, 36 (04) : 579 - 592
  • [29] Artificial intelligence (AI) learning tools in K-12 education: A scoping review
    Yim, Iris Heung Yue
    Su, Jiahong
    JOURNAL OF COMPUTERS IN EDUCATION, 2025, 12 (01) : 93 - 131
  • [30] Artificial intelligence (AI) learning tools in K-12 education: A scoping review
    Yim, Iris Heung Yue
    Su, Jiahong
    JOURNAL OF COMPUTERS IN EDUCATION, 2024, 12 (1) : 93 - 131