IHRAS:通过分类,细分和LLM从胸部X射线自动生成医疗报告
Gabriel Arquelau Pimenta Rodrigues1, André Luiz Marques Serrano1,2, Guilherme Dantas Bispo1
1Department of Electrical Engineering, University of Brasilia, Federal District, Brasília 70910-900, Brazil.
Bioengineering (Basel, Switzerland)
|August 28, 2025
概括
这项研究引入了智能化放射学分析系统 (IHRAS),用于自动化胸部X射线 (CXR) 分析和报告. 人工智能系统准确地解释胸部状况并生成结构化报告,帮助放射科医生.
科学领域:
- 医学成像
- 放射学中的人工智能
- 临床信息学
背景情况:
- 对于高效准确的胸部X射线 (CXR) 解释的需求日益增加.
- 需要人工智能解决方案来减少放射科医生的工作量和诊断变化.
- 在放射学工作流程中缺乏标准化,可解释的AI工具.
研究的目的:
- 引入智能化放射学分析系统 (IHRAS),用于自动化CXR分析和报告生成的AI框架.
- 评估IHRAS的诊断性能和报告质量.
- 展示一个透明和可扩展的AI解决方案来支持放射学工作流程.
主要方法:
- 开发IHRAS,一个集成深度卷积神经网络进行分类的模块化框架,用于可视化Grad-CAM,用于细分SAR-Net以及用于报告生成的大型语言模型 (DeepSeek-R1).
- 使用CRISPE快速工程框架以SNOMEDCT术语生成报告.
- 在NIH胸部X射线数据集上进行评估,评估诊断性能和报告质量指标 (忠实性,相关性,对齐性).
主要成果:
- 在不同的人口和临床小组中,IHRAS表现一致.
- 该系统生成了高准确性,临床相关的放射性报告.
- 报告的可信度,相关性和一致性得分很高.
结论:
- IHRAS为CXR分析和报告生成提供了一个自动化的端到端解决方案.
- 该系统提供了一个透明和可扩展的方法来支持放射性工作流程.
- 在临床人工智能应用中强调可解释性和标准化的重要性.
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