Evaluating OWL 2 reasoners in the context of clinical decision support in lung cancer treatment selection
Sesen MB., Jiménez-Ruiz E., Bañares-Alcántara R., Brady SM.
This paper evaluates the performances of the OWL 2 reasoners HermiT, FaCT++ and Pellet in the context of an ontological clinical decision support system in lung cancer care. In the first set of experiments, we compare how the classification and realisation times of the LUCADA and LUCADA-SNOMED CT ontologies vary as we expand their TBoxes with additional guideline rule knowledge. In the second set of experiments, we investigate the effect of increasing the ABox of the LUCADA ontology on the realisation times.