通过分布式数据驱动的语义服务和跨组织的工作流程,优化了持续的家庭护理供应
Mathias De Brouwer1, Pieter Bonte2, Dörthe Arndt3
1Department of Information Technology, IDLab - Ghent University - imec, 9052, Ghent, Belgium. Mathias.DeBrouwer@UGent.be.
Journal of biomedical semantics
|June 6, 2024
概括
使用语义网络技术的新架构优化了医疗保健协调,以获得更好的持续护理. 这种方法增强了家庭护理环境中的数据共享和个性化服务.
科学领域:
- 计算机科学 计算机科学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 医疗保健提供者之间越来越多的协作需要有效的数据和工作流协调,特别是在转向家庭护理时.
- 机器可解释和可重复使用的数据曝光对于最佳的患者护理至关重要.
- 需要智能,动态,个性化和高性能服务,具有符合质量限制的灵活工作流程.
研究的目的:
- 为医疗保健数据和工作流协调提供分布式,通用,级联推理参考架构.
- 展示用于数据驱动的语义服务和跨组织工作流程的语义网络技术的使用.
- 在一个现实的家庭护理场景中评估拟议的架构的性能和可用性.
主要方法:
- 使用语义网络工具实例化的参考架构:RMLStreamer用于链接数据生成,DIVIDE用于自适应查询,Streaming MASSIF用于服务部署,AMADEUS用于工作流组成.
- 使用RMLEditor和Matey进行链接数据生成的规则配置.
- 开发一个用例演示器,用于个性化的智能监控和跨组织的治疗规划.
主要成果:
- 监测管道有效地处理每秒14次观测.
- 像将JSON映射到RDF (13.5毫秒),发烧报警 (26.4毫秒) 和智能通知 (1539.5毫秒) 等关键操作表现良好.
- 治疗计划构建和冲突检测分别在190.8毫秒和1335.7毫秒内完成,证明了可行性.
结论:
- 现有的语义网络技术可以有效地利用,以优化持续的医疗保健供应.
- 评估证实了架构组件在家庭护理环境中的适用性,可用性和良好性能.
- 建议进一步开发用户界面,以加强工具的采用和集成.
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