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Medical Knowledge Morphing via a Semantic Web Framework Syed Sibte Raza Abidi and Sajjad Hussain
 

Summary: Medical Knowledge Morphing via a Semantic Web Framework
Syed Sibte Raza Abidi and Sajjad Hussain
NICHE Research Group, Faculty of Computer Science, Dalhousie University
Halifax, Canada
{sraza, hussain}@cs.dal.ca
Abstract
Clinical decision-making involves an active interplay between various medical knowledge
modalities. Medical knowledge morphing aims to support clinical decision support by
mimicking the interplay between knowledge modalities, as per the problem description, to
derive a holistic knowledge-base. We leverage the Semantic Web technology suite to pursue
knowledge morphing. We present a Knowledge Morphing framework that involves ontologies
to represent the domain and knowledge artifacts, annotation of knowledge artifacts based on
the respective ontological model, and ontology mediation activities to knowledge morphing.
1. Introduction
Clinical decision-making is a complicated activity because it involves a complex, multi-
faceted and dynamic interplay between patient parameters that evolve along a temporal axis,
medical knowledge withheld by the practitioner, procedural and operational constraints
defining the care environment, and health outcomes metrics [1, 2]. If one just considers the
medical knowledge component of clinical decision-making, then the complexity of the task
can be gauged by studying the underlying complex interplay between heterogeneous medical

  

Source: Abidi, Syed Sibte Raza - Faculty of Computer Science, Dalhousie University

 

Collections: Computer Technologies and Information Sciences