ArticleJournal of cancer education : the official journal of the American Association for Cancer Education2026
Using ChatGPT to Solve Clinical Radiobiology Problems.
Article in Journal of cancer education : the official journal of the American Association for Cancer Education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
ChatGPT is one of the most advanced large language models. We aim to examine ChatGPT-4o accuracy in solving radiobiology computational problems. Two board-certified radiation oncologists created a problem set consisting of 30 questions. We used OpenAI API to query the ChatGPT(model: GPT-4o) and generate corresponding answers. Answers were graded using a 3-score system. We conducted subgroup analysis for no prompts(zero-shot learning) and different prompts, questions with or without alpha-beta ratio, and question categories. ChatGPT correctly answered approximately 60% of questions without any prompting strategies. While ChatGPT demonstrates stable performance in structured calculation problems, particularly those involving alpha-beta ratios, it still exhibits notable limitations in handling multi-step reasoning and clinical decision-making tasks. This result highlights the need for integrating professional tools and refining prompting strategies to enhance their practical utility.
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42062655What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.