title: Developing a semantic web model for medical differential diagnosis recommendation.
abstract: In this paper we describe a novel model for differential diagnosis designed to make recommendations by utilizing semantic web technologies. The model is a response to a number of requirements, ranging from incorporating essential clinical diagnostic semantics to the integration of data mining for the process of identifying candidate diseases that best explain a set of clinical features. We introduce two major components, which we find essential to the construction of an integral differential diagnosis recommendation model: the evidence-based recommender component and the proximity-based recommender component. Both approaches are driven by disease diagnosis ontologies designed specifically to enable the process of generating diagnostic recommendations. These ontologies are the disease symptom ontology and the patient ontology. The evidence-based diagnosis process develops dynamic rules based on standardized clinical pathways. The proximity-based component employs data mining to provide clinicians with diagnosis predictions, as well as generates new diagnosis rules from provided training datasets. This article describes the integration between these two components along with the developed diagnosis ontologies to form a novel medical differential diagnosis recommendation model. This article also provides test cases from the implementation of the overall model, which shows quite promising diagnostic recommendation results.
authors.affiliation: Department of Software Engineering, Lakehead University, 955 Oliver Road, Thunder Bay, P7B 5E1, ON, Canada, omohamme@lakeheadu.ca.
authors.forename: Osama
authors.initials: O
authors.lastname: Mohammed
authors.forename: Rachid
authors.initials: R
authors.lastname: Benlamri
mesh_terms: D001185:Artificial Intelligence; D064229:Biological Ontologies; D003198:Computer Simulation; D019091:Critical Pathways; D057225:Data Mining; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D019317:Evidence-Based Medicine; D006801:Humans; D020407:Internet; D012660:Semantics; D012985:Software Design