Clinical Validation and Performance Evaluation of Ontology-Based Expert System in Emergency Medicine
Keywords:
Early Warning Scoring System (EWS), Emergency Department (ED) Ontology,Ontology web language (OWL), Expert System (ES), ProtégéAbstract
This manuscript presents the clinical validation and performance assessment of an ontology-driven expert system designed to assist emergency medical personnel in pre-hospital care scenarios. The system, structured using a semantic web framework and integrated with the National Early Warning Score (NEWS) methodology, aids in risk stratification, preliminary diagnosis, and treatment guidance for patients in critical condition. Built upon a modular client-server architecture using Java and OWL ontologies, the system captures vital parameters entered by emergency staff and infers risk levels through a rule-based ontology. Clinical validation was conducted in collaboration with a multispecialty hospital's emergency department, where real patient data was used to evaluate the system’s accuracy and practical relevance. Results demonstrate a significant correlation between the predicted risk levels and actual patient outcomes, confirming the system’s potential to enhance decision-making in time-sensitive medical emergencies. This paper discusses the implementation, testing methodology, outcome analysis, and practical implications of deploying such ontology-based systems in real-world emergency medical services.
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