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NIRS: An Ontology for Non-Invasive Respiratory Support in Acute Care

Created by
  • Haebom

Author

Md Fantacher Islam, Jarrod Mosier, Vignesh Subbian

Outline

This paper aims to develop an ontology for noninvasive respiratory support (NIRS) to support knowledge representation in emergency care settings. We used Web Ontology Language (OWL) semantics and Protege to structure clinical concepts and relationships, and added Semantic Web Rule Language (SWRL) rules to enable rule-based clinical reasoning beyond hierarchical structures. We evaluated logical reasoning by adding 17 hypothetical patient clinical scenarios, and searched and tested the targeted inferences using SPARQL queries and data from the Electronic Intensive Care Unit (eICU) Collaborative Research Database. The developed ontology comprises 882 axioms, 132 classes, 12 object properties, and 17 data properties, and 350 annotations were added to standardize clinical concepts. All test cases (rules) were successfully validated through SPARQL queries, retrieving relevant patient outcomes, such as the finding that patients treated with high-flow nasal cannula (HFNC) for 2 hours due to acute respiratory failure could avoid endotracheal intubation. In conclusion, this study integrated NIRS concepts into an ontology framework and demonstrated its applicability through evaluation of virtual patient scenarios and alignment with a standardized vocabulary.

Takeaways, Limitations

Takeaways:
Providing a standardized ontology for noninvasive respiratory support (NIRS).
Rule-based clinical reasoning support using OWL and SWRL.
Efficient data retrieval and analysis possible through SPARQL queries.
Establishing a foundation for consistent medical documentation and integrated clinical data models.
Presenting the possibility of advanced analysis of NIRS results.
Limitations:
Further validation of application in real clinical settings is needed, based on assessments based on virtual patient scenarios.
The evaluation was limited to the eICU database, and further studies are needed to determine applicability to other databases.
The need for continuous updating and maintenance of the ontology.
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