A Radiation Oncology Board Exam of ChatGPT
Andrew B Barbour1, T Aleksandr Barbour2
1Radiation Oncology, University of Washington - Fred Hutchinson Cancer Center, Seattle, USA.
Abstract:
As artificial intelligence (AI) models improve and become widely integrated into healthcare systems, healthcare providers must understand the strengths and limitations of AI tools to realize the full spectrum of potential patient-care benefits. However, most providers have a poor understanding of AI, leading to distrust and poor adoption of this emerging technology. To bridge this divide, this editorial presents a novel view of ChatGPT's current capabilities in the medical field of radiation oncology. By replicating the format of the oral qualification exam required for radiation oncology board certification, we demonstrate ChatGPT's ability to analyze a commonly encountered patient case, make diagnostic decisions, and integrate information to generate treatment recommendations. Through this simulation, we highlight ChatGPT's strengths and limitations in replicating human decision-making in clinical radiation oncology, while providing an accessible resource to educate radiation oncologists on the capabilities of AI chatbots.
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