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

Radiography (Lond). 2024 Mar;30(2):474-482. doi: 10.1016/j.radi.2023.12.019. Epub 2024 Jan 12.

Abstract

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 (∼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.

Keywords: Artificial intelligence; Education; Medical imaging; Radiography; Radiology.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence*
  • Curriculum
  • Diagnostic Imaging*
  • Educational Status
  • Humans
  • Radiography