智能医疗保健系统转型的本体学框架和挑战,使用自然语言处理和潜在的迪里克莱特分配
Shuyan Zhao1, Hua Zhong1, Beibei Ge1
1School of Management, Beijing Institute of Technology, Beijing, Peoples R China.
Health informatics journal
|September 18, 2025
概括
这项研究开发了一个智能医疗保健系统本体结构框架,使用隐性迪里克莱特分配 (LDA) 和自然语言处理 (NLP). 它确定了智能医疗转型的14个挑战,帮助未来的研究和实践.
科学领域:
- 医疗信息学 医疗信息学
- 知识工程知识工程知识工程
- 医疗保健中的人工智能
背景情况:
- 向智能医疗保健系统的转型需要对其组件和挑战有结构的理解.
- 现有的文献缺乏智能医疗保健系统的综合本体学框架.
- 学术界和从业人员需要一个参考模型来导航医疗保健系统的演变.
研究的目的:
- 为智能医疗保健系统开发一个本体学框架.
- 确定构建和实施智能医疗保健系统的关键挑战.
- 为智能医疗保健研究和实践提供结构化的知识基础.
主要方法:
- 系统性文献审查智能医疗出版物从科学网络核心集合.
- 隐性迪里克莱特分配 (LDA) 的应用,用于提取的出版物的主题建模.
- 使用自然语言处理 (NLP) 来提取实体并构建本体论.
- 使用Protégé软件,以OWL格式开发本体论.
主要成果:
- 成功开发了智能医疗保健系统的综合本体学框架.
- 确定了14个重大挑战,包括系统互操作性差,数据安全,数据共享问题和数据标准的低采用.
- 这些挑战为解决智能医疗实施中的潜在风险提供了路线图.
结论:
- 开发的本体结构框架为智能医疗保健系统提供了统一的描述和结构化的知识.
- 该框架为研究人员和医疗保健专业人员提供了有价值的工作方法和管理基础.
- 该研究强调了解决已确定的挑战的关键需求,以促进成功的智能医疗转型.
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