A conceptual framework for ontology based automating and merging of clinical pathways of comorbidities

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

In this paper we present a conceptual framework for ontology based knowledge representation and merging of Clinical Pathways (CP) of comorbidities. Paper based CP are static documents which do not have adaptability to accommodate dynamic changes in a patient's conditions, particularly in case of co-morbidity, since most CP are focused on a single disease management. Our approach to computerize and merge CP of comorbidities for decision support purpose include; 1. Representation of comorbidity CP as OWL ontologies, 2. Merging ontologies along common tasks, 3. Execution of merged ontology using OWL reasoner to provide CP mediated decision support, 4. Evaluation of recommendations by instantiating the ontology with comorbidity scenarios. Most challenging and unique aspect of this research is that it involves the dynamic integration of computerized CP of two concurrent comorbid diseases, whilst maintaining clinical pragmatics and medical correctness. We believe that Semantic Web has enormous potential to achieve this goal.

Original languageEnglish
Title of host publicationKnowledge Management for Health Care Procedures - ECAI 2008 Workshop, K4HelP 2008, Revised Selected Papers
Pages55-66
Number of pages12
DOIs
Publication statusPublished - 2009
EventECAI Workshop on Knowledge Management for Health Care Procedures, K4HelP 2008 - Patras, Greece
Duration: Jul 21 2008Jul 21 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5626 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceECAI Workshop on Knowledge Management for Health Care Procedures, K4HelP 2008
Country/TerritoryGreece
CityPatras
Period7/21/087/21/08

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

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