将人工智能结果自动集成到放射学报告中,使用共同的数据元素
Garv Mehdiratta1, Jeffrey T Duda1, Ameena Elahi2
1Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St., Philadelphia, PA, 19104, USA.
共同数据元件 (CDE) 允许将人工智能 (AI) 测量无集成到放射学报告中. 这种标准化框架提高了数据的一致性,互操作性和AI驱动的医疗保健见解的通信.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 放射学 信息学 信息学
背景情况:
- 人工智能 (AI) 具有提高放射学诊断准确度和工作流程效率的潜力.
- 将人工智能衍生测量集成到放射学报告中,需要标准化数据格式以实现无整合.
- 共同数据元件 (CDE) 为可互操作的健康信息提供了一个标准化的框架.
研究的目的:
- 描述CDE的应用,将AI衍生测量嵌入到放射学报告中.
- 定义一组用于肝脏和脏体积和衰减测量的CDE.
- 证明在临床实践中使用CDE用于AI数据传输.
主要方法:
- 一个人工智能系统在非对比CT图像上对肝脏和脏进行了细分.
- 用DICOM-SR框架将人工智能生成的测量记录为CDE.
- 自动化系统提取了CDE,将其纳入报告中,并将图像发送到PACS.
主要成果:
- 人工智能系统成功地对腹部器官进行了细分,并产生了体积和衰减测量.
- 从AI数据中成功提取了CDE标签和值,并集成到放射学报告中.
- 这个过程使得人工智能生成的图像系列能够传输到PACS.
结论:
- 放射学CDE为记录和传输人工智能生成的数据提供了实际框架.
- 这种方法增强了沟通,促进了研究,并改善了决策支持系统.
- 医疗保健中心确保在医疗保健系统中报告人工智能发现的一致性,互操作性和清晰度.
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