评估大语言模型用于结节成像推:双子座,副驾驶员和ChatGPT-4.0的比较分析
Yavuz Yigit1,2, Asım Enes Ozbek3, Betul Dogru3
1Department of Emergency Medicine, Hamad Medical Corporation, Doha, 3050, Qatar.
International journal of emergency medicine
|July 4, 2025
概括
与Copilot和ChatGPT-4.0相比,Gemini在医学成像建议方面与专家的共识保持了更好的一致性,这表明它作为可靠的临床决策工具的潜力.
科学领域:
- 医疗信息学医学信息学
- 医疗保健中的人工智能
- 自然语言处理 (NLP) 是一种自然语言处理.
背景情况:
- 自然语言处理 (NLP) 已经取得了重大进展,大型语言模型 (LLM) 现在对医疗挑战至关重要.
- 在临床决策支持系统中,LLM的潜力越来越被探索.
研究的目的:
- 评估三个著名的LLM (Gemini,Copilot,ChatGPT-4.0) 与专家共识的协调情况.
- 专注于对呈现急性侧侧疼痛的患者的成像建议.
主要方法:
- 使用了29个临床图片,这些图片具有不同的患者人口统计和临床情景.
- 对LLM的回应与多专业小组的共识建议进行了比较.
- 主要结果:与多数共识相匹配的LLM响应率;次要结果:与完美/优秀评级和个人评审者协议一致.
主要成果:
- 双子座实现了65.5%与多数共识一致,超过了Copilot和ChatGPT-4.0 (41.4%).
- 双子座在完美/优秀场景中显示了69.5%的同意,明显高于Copilot和ChatGPT-4.0 (43.4%).
- 双子座的同意率为82.7%,这表明它在复杂的医疗调查中具有更高的能力.
结论:
- 双子座的表现始终优于Copilot和ChatGPT-4.0在与专家共识对准急性侧翼疼痛成像推方面.
- 双子座显示出作为放射学临床决策的可靠工具的潜力.
- 进一步的研究是必不可少的,以提高法学士的可靠性,准确性,并解决医疗整合的伦理/法律方面的考虑.
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