Thinking PubMed: an innovative system for mental health domain

Hadzic, Maja and D'Souza, Russel and Hadzic, Fedja and Dillon, Tharam. 2008. Thinking PubMed: an innovative system for mental health domain, in Puuronen, S. and Pechenizkiy, M. and Tsymbal, A. and Lee, D.J. (ed), 21st IEEE International Symposium on Computer Based Medical Systems, Jun 17 2008, pp. 330-335. Jyvaskyla, Finland: Institute of Electrical and Electronics Engineers (IEEE) Computer Society

Source Title

Proceedings of 21st IEEE international symposium on computer based medical systems (CBMS 2008)

Source Conference

21st IEEE International Symposium on Computer Based Medical Systems (CBMS 2008)

DOI

10.1109/CBMS.2008.20

ISBN

9780769531656

Faculty

Curtin Business School

School of Economics and Finance

School

Centre for Extended Enterprises and Business Intelligence

Remarks

Copyright © 2008 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

URI

http://hdl.handle.net/20.500.11937/25258

Collection

Curtin Research Publications

Abstract

Information regarding mental illness is dispersed over various resources but even within a specific resource, such as PubMed, it is difficult to link this information, to share it and find specific information when needed. Specific and targeted searches are very difficult with current search engines as they look for the specific string of letters within the text rather than its meaning.In this paper we present Thinking PubMed as a system that results from synergy of ontology and data mining technologies and performs intelligent information searches using the domain ontology. Furthermore, the Thinking PubMed analyzes and links the retrieved information, and extracts hidden patterns and knowledge using data mining algorithms. This is a new generation of information-seeking tool where the ontology and data-mining work in concert to increase the value of the available information.