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Artificial intelligence in radiology: trainees want more.

O-U Hashmi1, N Chan2, C F de Vries3

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UK radiology trainees show strong interest in artificial intelligence (AI) and demand AI education. Despite limited current training, most trainees believe AI will enhance diagnostic radiology and want to participate in AI projects.

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Area of Science:

  • Medical Imaging and Radiology
  • Artificial Intelligence in Healthcare
  • Medical Education Technology

Background:

  • Artificial intelligence (AI) is rapidly evolving, with significant potential to impact various medical fields, including radiology.
  • Understanding the perspectives of future radiologists is crucial for integrating AI effectively into clinical practice and education.

Purpose of the Study:

  • To assess the attitudes of UK radiology trainees regarding the use of artificial intelligence (AI) in radiology.
  • To determine the demand for AI education among radiology trainees in the UK.

Main Methods:

  • A survey was developed using Google Forms and distributed via email to all UK radiology training programs.
  • The survey collected responses from 149 trainee radiologists across all UK training programs over two months.

Main Results:

  • A high percentage of trainees (83.7%) expressed interest in AI in radiology, with 79.9% wanting to be involved in AI projects.
  • Nearly all respondents (98.7%) agreed AI should be taught in radiology training, yet only one program reported implementing AI teaching.
  • Trainees prioritized learning basic understanding, implementation, and critical appraisal of AI software, with 74.2% believing AI will enhance diagnostic radiology in 20 years.

Conclusions:

  • UK radiology trainees exhibit predominantly positive attitudes towards AI, with significant interest in AI-related projects, activities, and education.
  • There is a clear demand for AI education within UK radiology training programs, despite the current limited availability of such training.
  • Addressing trainees' concerns regarding IT/implementation and ethical/regulatory issues will be vital for successful AI integration.