RadGPT:一个基于大型语言模型的系统,生成以患者为中心的材料集,以解释放射学报告信息
Sanna E Herwald1, Preya Shah1, Andrew Johnston1
1Department of Radiology, Stanford Medicine, 300 Pasteur Drive, Stanford, CA, USA.
Journal of the American College of Radiology : JACR
|June 12, 2025
概括
使用人工智能的新系统RadGPT通过生成清晰的解释和问答对来提高患者对复杂放射学报告的理解. 该工具可确保患者获得准确,安全和个性化的医疗信息.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 患者教育 患者教育
背景情况:
- "治疗法"规定患者可以实时访问放射学报告.
- 放射学报告通常包含技术语言,妨碍患者的理解.
- 弥合理解差距对于知情的患者参与至关重要.
研究的目的:
- 评估RadGPT,一个集概念提取和大型语言模型 (LLM) 的新系统,以改善患者对放射学报告的理解.
- 评估来自放射学报告的AI生成的解释和问答对的质量和安全性.
主要方法:
- RadGPT从30个放射学报告的印象中生成了概念解释和问答对.
- 使用LLM生成问题和解释,有或没有概念提取.
- 放射学专业人员使用标准化标签对生成材料的质量进行评分.
主要成果:
- 由RadGPT生成的材料,特别是基于LLM的问答对,从专家评级者那里获得了高评分 (>95%).
- 通过LLM生成的问题显示质量明显高于模板生成的问题 (p < 0.001).
- 没有任何生成的内容被认为是不安全的或可能影响患者护理;50%以上获得了最高的排名.
结论:
- RadGPT有效地为放射学报告生成高质量,个性化的教育内容.
- 该系统是安全的,并可能提高患者对医学成像结果的理解.
- 这种人工智能工具支持改善患者参与和遵守治疗法要求.
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