Ontology based recommender system for first aid emergency response

Basic life support is usually provided to the victim under medical emergencies by trained professionals. But under situations where trained professionals are not available, it is also not wise to rely on untrained people. Therefore, it is highly desirable to utilize advanced technology that can assist the untrained rescuer in providing first aid. The recommender systems can be one of the potential tools in saving life. Ontologies have provided the means for such systems to learn from their environment which is highly desired in this context. The main aim of this paper is to propose and develop ontology-based recommender system for medical emergency life support. The system’s knowledge inference is based on OWL ontology that is developed using Protégé as semantic engine and SPARQL to generate ontology rules in rule engine. Other components are knowledgebase and user interaction panel which are implemented using MySQL and PHP for validation purposes. The ontology defines the symptoms under well accepted ABC protocol and the desired actions are linked according to American Heart Association (AHA). Various emergency cases are tested and the results are benchmarked with AHA and other existing literature. Furthermore, the medical expert judgements are acquired about the results to validate the effectiveness.