A Radiation Oncology Board Exam of ChatGPT

• Published in: Curēus (Palo Alto, CA) Vol. 15; no. 9; p. e44541
• Main Authors: Barbour, Andrew B, Barbour, T. Aleksandr
• Format: Journal Article
• Language: English
• Published: Palo Alto Cureus Inc 01-09-2023; Cureus
• Subjects: Biopsy; Cancer therapies; Chatbots; Diagnostic tests; Healthcare Technology; Language; Life expectancy; Medical Education; Medical personnel; Multidisciplinary teams; Oncology; Patients; Prostate cancer; Radiation Oncology; Radiation therapy; Scintigraphy; Surgery; Surveillance
• ISSN: 2168-8184; 2168-8184
• DOI: 10.7759/cureus.44541

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.