Université Sorbonne Paris Nord, LIMICS, Sorbonne Université, INSERM, UMR 1142, F-93000, Bobigny, France.
Stud Health Technol Inform. 2024 Aug 22;316:1427-1431. doi: 10.3233/SHTI240680.
The task of managing diverse electronic health records requires the consolidation of data from different sources to facilitate clinical research and decision-making support, with the emergence of the Observational Medical Outcomes Partnership - Common Data Model (OMOP-CDM) as a standard relational database schema for structuring health records from different sources. Working with ontologies is strongly associated with reasoners. Implementing them over expansive and intricate Ontologies can pose computational challenges, potentially resulting in slow performance. In this paper, we propose the implementation of a new reasoner based on categorical logic over a translation of OMOP-CDM into an ontology model. This enables enhancements to the efficiency and scalability of implementing such models.
管理多样化的电子健康记录需要整合来自不同来源的数据，以促进临床研究和决策支持，而观察性医学结局伙伴关系-通用数据模型（OMOP-CDM）的出现则为来自不同来源的健康记录构建标准关系数据库模式。与推理机配合使用与本体密切相关。在广泛而复杂的本体上实现它们可能会带来计算上的挑战，从而导致性能缓慢。在本文中，我们提出了在基于范畴逻辑的新推理机上实现的方案，该推理机基于将 OMOP-CDM 转换为本体模型。这可以提高实现此类模型的效率和可扩展性。
