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Vol: 58(72) No: 1 / March 2013 Towards Gathering Knowledge for Clinical Decision Support Systems with Topic Maps Daniel Dragu “Politehnica” University of Timisoara, Faculty of Automation and Computers, Bd. V. Parvan 2, 300223, Timisoara, Romania, e-mail: daniel.dragu@aut.upt.ro Valentin Gomoi “Politehnica” University of Timisoara, Faculty of Automation and Computers, Bd. V. Parvan 2, 300223, Timisoara, Romania, e-mail: valentin.gomoi@aut.upt.ro Vasile Stoicu-Tivadar “Politehnica” University of Timisoara, Faculty of Automation and Computers, Bd. V. Parvan 2, 300223, Timisoara, Romania, e-mail: vasile.stoicu-tivadar@aut.upt.ro Keywords: semantics, clinical decision support systems, Topic Maps, knowledge representation, Virtual Medical Records Abstract Over time, there were used various data storage models: text files, comma separated values, hierarchical databases, relational databases, graph databases and so on. The rapid expansion of the web has given rise to new challenges, like navigating through lots of documents, through large amount of data, or retrieving the information. In this context, semantic technologies came as a solution, promising full data interchangeability between hardware and software entities of the web. E-health keeps up with the latest advances in information and communication technologies and the involved researchers pay their special attention to finding optimal solutions for the knowledge management, in order to obtain better outcome of the automated systems in healthcare. Improving the results of the Clinical decision support systems (CDSs) is a permanent concern for many research communities, which have to deal with an abundance of data and applications, structures and methods, tools and other entities specific to all of the disciplines involved in e-health. CDSs are developed based on medical experts’ knowledge and they are designed to assist clinicians to improve healthcare act. The paper presents a method to obtain more refined medical recommendations by enriching the inputs of the CDSs, through a semantic integration of several medical knowledge sources, by using a semantic technology, the Topic Maps standard. Future research directions and challenges are summarized and conclusions are issued. References [1] T. Berners-Lee, J. Hendler, and O. Lassila, “The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities”, Scientific American, May 2001. [2] Health Level Seven International, Inc., Available from http://www.hl7.org. [3] K. Kawamoto (2011) “Virtual Medical Record (vMR) for Clinical Decision Support– Domain Analysis Model” – HL7 Project #184 Informative Ballot, Available from http://wiki.hl7.org/images/7/71/HL7vMR_vMR_Domain_Analysis_Model_Release_1.pdf. [4] ISO 13250: Topic Maps, Topic Maps — Data Model. Available from http://www.isotopicmaps.org/sam/sam-model/2008-06-03/ [5] S. Pepper (2009) “Topic Maps”. Encyclopedia of Library and Information Sciences, Third Edition. doi: 10.1081/E-ELIS3-120044331. [6] R. Cerny, “Topincs: A Software for Rapid Development of Web Databases”. KMIS 2011 - Proceedings of the International Conference on Knowledge Management and Information Sharing pp. 187-194. SciTePress 2011. [7] L.M. Garshol, “Towards a Methodology for Developing Topic Maps Ontologies”. in: Maicher L, Sigel A, Garshol LM (eds.) Leveraging the Semantics of Topic Maps, Second International Conference on Topic Maps Research and Applications TMRA 2006. LNCS (LNAI), vol. 4438, Springer, Heidelberg 2007. [8] W3C Recommendation 10 February 2004, “Resource Description Framework (RDF): Concepts and Abstract Syntax”, Available from http://www.w3.org/TR/rdf-concepts/. [9] W3C Recommendation 27 October 2009, “ OWL 2 Web Ontology Language Document Overview”, Available from http://www.w3.org/TR/owl2-overview/. [10] V. Gomoi, D. Dragu and V. Stoicu-Tivadar, “Clinical Decision Support Based on Topic Maps and Virtual Medical Record”, The First International Conference on Intelligent Systems and Applications (INTELLI 2012), France, 2012, pp. 71-75. [11] D. Dragu, V. Gomoi and V. Stoicu-Tivadar, “Topic Maps as knowledge base to automatically generate medical Recommendations”, 2011 IEEE 9th International Symposium on Intelligent Systems and Informatics (SISY 2011); Subotica, Serbia, September 2011, pp. 459-464. [12] D. Dragu, V. Gomoi and V. Stoicu-Tivadar, “Using Topic Maps to Gather Knowledge for Clinical Decision Support Systems”, Innovation and Cooperation, Proceeding of Conference of the Romanian Society of Medical Informatics (ROMEDINF2012), Timișoara, Romania, November 15-17, 2012. [13] L. Stoicu-Tivadar, F. Sicurello, V. Moga, M. moga, G. 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