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Could ChatGPT Pass the UK Radiology Fellowship Examinations?

Sisith Ariyaratne1, Nathan Jenko1, A Mark Davies1

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Artificial intelligence (AI) models like ChatGPT demonstrate significant potential in medical examinations. While ChatGPT narrowly missed passing the UK radiology fellowship physics exam, GPT-4 successfully passed the clinical radiology exam, indicating AI

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Area of Science:

  • Artificial Intelligence
  • Machine Learning
  • Medical Education

Background:

  • Artificial intelligence (AI) tools, such as ChatGPT, leverage machine learning for human-like text generation.
  • AI models show increasing proficiency in complex problem-solving, including professional examinations.
  • The performance of AI in medical assessments is an emerging area of research.

Purpose of the Study:

  • To evaluate the performance of ChatGPT on UK radiology fellowship equivalent examination questions.
  • To assess the capabilities of different versions of ChatGPT (GPT-3.5 and GPT-4) in a high-stakes medical examination context.

Main Methods:

  • ChatGPT was tasked with answering questions from Fellowship of the Royal College of Radiologists (FRCR) examination question banks.
  • The GPT-4 model answered 203 true/false questions from the physics part 1 exam.
  • Both GPT-3.5 and GPT-4 models answered 240 single best answer (SBA) questions from the FRCR 2A examination.

Main Results:

  • ChatGPT-4 achieved 74.8% accuracy on the physics part 1 exam, narrowly missing the 75.5% passing mark.
  • In the FRCR 2A examination, GPT-3.5 scored 50.8% and GPT-4 achieved 74.2%.
  • GPT-4's score of 74.2% surpassed the 63.3% passing mark for the winter 2022 2A exam.

Conclusions:

  • AI models, including ChatGPT, can successfully answer a majority of questions in FRCR-style examinations.
  • Further advancements in AI are expected to enhance their ability to comprehend and solve medical and clinical radiology questions.
  • These findings highlight the growing role of AI in medical training, evaluation, and practice, with significant implications for radiology.