Abstract
Clinical Decision Support System (CDSS) can be used to prepare diagnosis from different patient’s details and hence physicians or nurses can review this diagnosis for improving the final decision. Due to the lack of CDSS in diabetes and related diseases in Sultanate of Oman, an Ontology based CDSS is proposed here. The deployed key components of the system are Adaptive Questionnaire Ontology, patient’s semantic profile, guideline ontology and risk assessment reasoner. We here propose a model for gathering the patient medical history based on dynamic questionnaire ontology. Ontology is among the most powerful tools to encode medical knowledge semantically. It is an abstract model which represents a common and shared understanding of a domain. The model is explained and implemented for diabetes domain.
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References
Ahmadian, L. Cornet, Ronald1; de Keizer, Nicolette F.1 Facilitating pre-operative assessment guidelines representation using SNOMED CT, Journal of Biomedical Informatics, Volume 43, Issue 6, pp. 883-890, (2010)
J. W. Bachman. The patient-computer interview: a neglected tool that can aid the clinician. Mayo Clinic Proceedings,78:67–78, (2003)
Sherimon P.C., Vinu P.V., Reshmy Krishnan, Development Phases of Ontology for an Intelligent Search System for Oman National Transport Company, In Proceeding(s) of the International Journal of Research and Reviews in Artificial Intelligence—IJRRAI, Vol 1, No.4, December, pp. 97-101, ISSN: 2046-5122, (2011)
Matt-Mouley Bouamrane, Alan Rector, Martin Hurrell, Ontology-Driven Adaptive Medical Information Collection System, Foundations of Intelligent Systems, Lecture Notes in Computer Science Volume 4994, pp 574-584, (2008)
Bouamrane M-mouley, Rector A, HurrellM (2008): Gathering Precise Patient Medical History with an Ontology-driven Adaptive Questionnaire. 2008:539-541.
Matt-Mouley Bouamrane, Alan Rector, Martin Hurrell, Development of an ontology for a preoperative risk assessment clinical decision support system. In Computer-Based Medical Systems, IEEE International Symposium, (2009)
Vinu P.V, Sherimon P.C., Reshmy Krishnan, Development Of Seafood Ontology For Semantically Enhanced Information Retrieval, International Journal of Computer Engineering and Technology, Volume 3, Issue 1, January- June, pp. 154-162 (2012)
Noy, N., McGuinness, D.: Ontology development 101: A guide to creating your first ontology, Technical Report SMI-2001-0880, Stanford Medical Informatics (SMI), Department of Medicine, Stanford University School of Medicine (2001)
Kamran Farooq, Amir Hussain, Stephen Leslie, Chris Eckl, Calum MacRae, Warner Slack, “An Ontology Driven and Bayesian Network Based Cardiovascular Decision Support Framework”, Advances in Brain Inspired Cognitive Systems, Lecture Notes in Computer Science Volume 7366, 2012, pp 31-41.
Warner V. Slack, M.D., Phillip Hicks, Ph.D., Charles E. Reed et al. A computer Based Medical History System N Engl J Med; 274:194-198,(1966)
R.Subhashini, Dr. J. Akilandeswar, A Survey on Ontology Construction Methodologies, International Journal of Enterprise Computing and Business Systems, 2011
Sherimon P.C., Vinu P.V., Reshmy Krishnan, Youssef Takroni, Developing a Survey Questionnaire Ontology for the Decision Support System in the Domain of Hypertension, IEEE South East Conference, April 4-7, Florida, U.S. (2013)
Sherimon P.C., Vinu P.V., Reshmy Krishnan, Youssef Takroni, Ontology Based System Architecture to Predict the Risk of Hypertension in Related Diseases, Accepted in International Journal of Information Processing and Management (ISSN: 2093-4009), (2013)
Matt-Mouley Bouamrane,Alan Recter,Martin Hurrel(2008) :Using Ontologies for an intelligent Patient modeling,Adaptation and management system:OTM 2008,part II,LNCS 5332,pp.1458-1470
S. Abidi, “Ontology-based knowledge modeling to provide decision support for comorbid diseases,” Knowledge Representation for Health-Care, pp. 27-39, 2011.
Acknowledgments
This work is published as part of a project funded by The Research Council [TRC], Oman under Agreement No. ORG/AOU/ICT/11/015, Proposal No ORG/ICT/11/004 and Arab Open University, Oman Branch.
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Sherimon, P.C., Vinu, P.V., Krishnan, R., Takroni, Y., AlKaabi, Y., AlFars, Y. (2014). Adaptive Questionnaire Ontology in Gathering Patient Medical History in Diabetes Domain. In: Herawan, T., Deris, M., Abawajy, J. (eds) Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering, vol 285. Springer, Singapore. https://doi.org/10.1007/978-981-4585-18-7_51
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DOI: https://doi.org/10.1007/978-981-4585-18-7_51
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