title: Comparing Drools and ontology reasoning approaches for telecardiology decision support.
abstract: Implantable cardioverter defibrillators can generate numerous alerts. Automatically classifying these alerts according to their severity hinges on the CHA2DS2VASc score. It requires some reasoning capabilities for interpreting the patient's data. We compared two approaches for implementing the reasoning module. One is based on the Drools engine, and the other is based on semantic web formalisms. Both were valid approaches with correct performances. For a broader domain, their limitations are the number and complexity of Drools rules and the performances of ontology-based reasoning, which suggests using the ontology for automatically generating a part of the Drools rules.
authors.affiliation: Inserm U936, Université de Rennes 1, Rennes, France.
authors.forename: Pascal
authors.initials: P
authors.lastname: Van Hille
authors.forename: Julie
authors.initials: J
authors.lastname: Jacques
authors.forename: Julien
authors.initials: J
authors.lastname: Taillard
authors.forename: Arnaud
authors.initials: A
authors.lastname: Rosier
authors.forename: David
authors.initials: D
authors.lastname: Delerue
authors.forename: Anita
authors.initials: A
authors.lastname: Burgun
authors.forename: Olivier
authors.initials: O
authors.lastname: Dameron
mesh_terms: D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006333:Heart Failure / Q000175:diagnosis* / Q000517:prevention & control; D006801:Humans; D012984:Software; D017216:Telemedicine / Q000379:methods*