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Radiology oral boards coach: A custom large language model prompt for structured oral board preparation in resident
Mahmoud Omar1, Komal Awan1, Nikhil Ramaiya1
1University Hospitals Cleveland Medical Center, Department of Radiology, 11100 Euclid Ave Cleveland, OH 44106, USA; Case Western Reserve University School of Medicine, Health Education Campus, 9501 Euclid Ave, Cleveland, OH 44106, USA.
Abstract:
With the reinstatement of the American Board of Radiology (ABR) oral board examination, optimal preparation strategies for the reinaugural classes remain undefined. Many radiology faculty, who are the cornerstone of residents' education, lack time availability and prior exposure to the oral exam format, creating a need for efficient, scalable training tools. Case readouts are a daily practice in which radiology residents and faculty collaboratively review unreported imaging studies, serving as the primary means of faculty-to-resident education outside of formal lectures. Large language models (LLMs), such as ChatGPT and OpenEvidence, can simulate human conversation and are revolutionizing education. We demonstrate the utility of LLMs as a framework for simulating oral board cases during readouts. Models can be created incorporating ABR preparation materials and the established one-minute preceptor technique to enable structured, efficient use in clinical workflows. We present custom instructions that can be copied into ChatGPT, OpenEvidence, or the preceptor's preferred LLM and are readily accessible for faculty to utilize in daily routine resident readouts. The aspired objective is for the "Radiology Oral Board Coach" to assist the busy radiology faculty in preparing future oral board candidates and ideally enhance residents' education and dictation proficiency.
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