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An ontology-based tool for modeling and documenting events in neurosurgery
Patricia Romao1, Stefanie Neuenschwander1, Chantal Zbinden2
1Bern University of Applied Sciences, Bern, Switzerland.
This study developed an ontology-based tool to improve intraoperative neurophysiological monitoring (IOM) documentation. The tool enhances data quality, aiding clinical decisions and research in neurosurgery.
Area of Science:
- Biomedical Informatics
- Neurosurgery
- Ontology Engineering
Background:
- Intraoperative neurophysiological monitoring (IOM) is crucial for patient safety in neurosurgery.
- Effective documentation of IOM events is challenging.
- An ontology-based tool was developed to address this documentation gap.
Purpose of the Study:
- To develop and evaluate an ontology-based tool for semantically enriched documentation of IOM events.
- To improve the quality and standardization of IOM data.
- To facilitate better clinical decision-making and research in neurosurgery.
Main Methods:
- Ontology development following Open Biological and Biomedical Ontology (OBO) principles.
- Agile software development for tool prototyping.
- Practical evaluation in real-world documentation settings.
Main Results:
- The IOM Documentation Ontology (IOMDO) integrates concepts from FMA, HPO, and OntoSPM.
- A user-friendly software tool was developed using JavaFX and Apache Jena.
- Test users found the tool accessible and usable.
Conclusions:
- The ontology-based tool enhances IOM documentation quality and standardization.
- Semantically enriched data supports informed decision-making and research.
- Addressing modeling issues in the Ontology of Adverse Events is key for optimization.
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