通过日本的专业认证考试,评估放射治疗中大型语言模型的能力
Noriyuki Kadoya1, Yoshiyuki Takahashi1, Seiya Koga1
1Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan.
Journal of radiation research
|January 10, 2026
概括
大型语言模型 (LLM) 在放射治疗知识方面表现强,ChatGPT-5 Pro在日本认证考试中达到90%以上的准确性. 这表明人工智能在医学物理学和放射性瘤学应用中集成的巨大潜力.
科学领域:
- 医学物理和辐射瘤学 医学物理和辐射瘤学
- 人工智能在医学中的应用
背景情况:
- 大型语言模型 (LLM) 展示了先进的自然语言理解能力.
- 越来越多的LLM正在被探索用于包括医学在内的专业领域的应用.
研究的目的:
- 为了评估几个LLM在放射治疗领域的特定领域的知识.
- 为了评估日本医学认证考试的LLM成绩.
主要方法:
- 五个LLM (ChatGPT-5,ChatGPT-5 Pro,Grok 4,Grok 4重,Gemini 2.5 Pro) 进行了测试.这些LLM的使用情况包括:
- 使用了来自日本三个放射治疗认证考试的多项选择题.
- 人工智能生成的答案与专家确定的参考答案进行了比较.
主要成果:
- 所有评估的LLM都实现了超过75%的准确性.
- 聊天GPT-5 Pro显示了最高的平均准确率,为94.7%±2.1%.
- 在不同模型和考试中,LLM准确率从78.4%到94.7%不等.
结论:
- 高级LLM拥有大量的放射治疗领域知识.
- 聊天GPT-5 Pro表现出卓越的性能,超过90%的准确性.
- 现有LLM显示出将其整合到放射治疗工作流程中的潜力,例如自动轮和治疗规划.
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