开发和应用中医医学本体论,用于糖尿病
Jie Hu1, Zixian Huang2, Xuewen Ge1
1Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China.
BMC medical informatics and decision making
|January 19, 2024
概括
通过使用多种数据源和先进的方法,开发出了一种新的中国糖尿病类天体学 (CDMO). 这种本体学增强了中国背景下糖尿病护理的AI应用,改善了临床决策支持和医疗问题答案.
科学领域:
- 生物医学信息学 生物医学信息学
- 本体学 工程学 工程学
- 医疗保健中的人工智能
背景情况:
- 对于推进医疗人工智能而言,对高质量的中文生物医学本体学的需求至关重要.
- 现有的本体学往往缺乏足够的细节性或中国医疗数据的特定文化/语言背景.
- 开发强大的实体学对于改善中国医疗保健中的临床决策支持和自然语言处理至关重要.
研究的目的:
- 开发一个全面的中国糖尿病类天体学 (CDMO).
- 探索和验证构建高质量的中国生物医学本体学的高效方法.
- 展示CDMO在人工智能驱动的医疗保健应用中的实用性.
主要方法:
- 综合自上而下和自下而上构建策略,使用各种数据来源:临床指南,专家共识,文献和医院数据库.
- 采用文本挖掘和跨语言的本体学映射,以实现强大的知识整合和质量提升.
- 使用临床专家和本体学开发工具验证了CDMO,评估其在临床决策支持和医疗问题答案中的应用.
主要成果:
- CDMO包括3,752个类和182个对象属性与等级关系,以及广泛的注释和超过12,000个映射到英语的本体学.
- 开发了200条糖尿病管理规则 (诊断,治疗,饮食,药物) 使用基于CDMO的语义网络规则语言.
- 通过整合CDMO知识,证明了T5模型在中国医疗问题中改善了糖尿病的性能.
结论:
- CDMO为中国医疗人工智能提供了坚实的基础,包括知识图和临床决策支持系统.
- 开发工作流程,包括NLP和跨语言映射,提高了本体学质量和效率.
- 这种方法作为创建其他高质量的非英语医学本体学的宝贵参考.
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