开发使用数字病理学和SNOMED-CT的国家病理学培训系统
Clare McGenity1,2, Alyn Cratchley1, Jocelyn Aldridge1
1Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Journal of pathology informatics
|July 21, 2025
概括
一个新的数字病理学资源为培训标准化病例分类. 该系统将组织病理学术语映射到SNOMED CT,创建可搜索的病理学教育和检查目录.
科学领域:
- 数字病理学数字病理学
- 医学教育 医学教育
- 组织病理学 组织病理学
背景情况:
- 数字病理学提供了宝贵的教育资源.
- 目前的局限性包括在案例检索和训练分类方面缺乏标准化.
研究的目的:
- 开发一个标准化系统来对数字病理学教学案例进行分类.
- 为病理学培训创建一个可搜索的教育案例目录.
主要方法:
- 开发了1600多个组织病理学教学术语.
- 将这些术语映射到SNOMED CT.
- 在国家数字病理学项目中将术语集成到临床PACS系统中.
主要成果:
- 创建了一个大型的数字病理学教学案例目录,与SNOMED CT术语相关.
- 产生了大量的教育案例目录.
- 该目录可以根据培训和考试的术语进行搜索.
结论:
- 成功开发了一个标准化的数字病理学教学案例目录,使用SNOMED CT术语.
- 该资源将被共享,以提高其在医疗保健提供者之间的效用.
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