A SEMANTIC WEB BASED APPROACH FOR DIAGNOSING RELATED HORMONE IMBALANCES
Abstract
Hormones are chemical messengers of the body that regulate bodily functions. Symptoms like depression, anxiety, and fatigue are caused by hormones going out of balance. In this study, we built a system that diagnoses three hormone imbalances (Testosterone, Thyroid Hormone, and Cortisol Hormone). The system makes use of a knowledge base built using the Web Ontology Language (OWL) and it interacts with the knowledge base using Jena API because it provides an ontology API for connecting to the ontology, generic reasoner serving as the inference engine, and SPARQL implementation for performing statistical queries. The benefits of this approach over an existing expert based system are improved ontology model by 71% in terms of knowledge representation and 58% in terms of taxonomy, ability to share patient data by moving them from MySQL database into the ontology, and ability to diagnose three related hormone imbalances
References
Bucci, G., Sandrucci, V. and Vicario, E. (2011). Ontologies and Bayesian Networks in Medical Diagnosis: Proceedings of the 44th Hawaiian Conference on System Sciences, (Edited by Sprague, R.H. (Jr)). IEEE Computer Society Press, pp. 1-8
Catwell, L., & Sheikh, A. (2009). Evaluating eHealth interventions: the need for continuous systemic evaluation. PLoS medicine, 6(8), e1000126.
Chandrasekaran, B., Josephson, J. R., &Benjamins, V. R. (1999). What are ontologies, and why do we need them?.IEEE Intelligent Systems and their applications, 14(1), 20-26.
Chang, Y., Fan, C., Lo, W., Hung, W. and Yuan,. S. (2014): Mobile Cloud-Based Depression Diagnosis using an Ontology and a Bayesian Network, Future Generations Computer Systems, Vol 32, pp. 87-98
Dandona, P. and Rosenberg, M. T. (2010). A Practical Guide to Male Hypogonadism in the Primary Care Setting, The International Journal of Clinical Practice, Vol 64, pp. 682-696
Garets, D., & Davis, M. (2006). Electronic medical records vs. electronic health records: yes, there is a difference. HIMSS Analytics, 2-14.
Manouselis, N., Sicilia, M. A., and Rodríguez, D. (2010). Exploring ontology metrics in the biomedical domain. Procedia Computer Science, 1(1), 2319-2328.
Marieb, E. N. (1992). Human Anatomy and Physiology: Benjamin/Cummings Publishing Company, pp. 548-549
Musen, M. A. (2015). The Protégé project: A look back and a look forward. AI matters, 1(4), 4-12
Oh, H., Rizo, C., Enkin, M. and Jadad, A. (2005). What IseHealth (3): A Systematic Review of Published Definitions, Journal of Medical Internet Research, Vol 7:1
Paganelli, F. and Giuli, D. (2013). An Ontology Based System for Context-Aware and Configurable Services to Support Home Based Continuous Care, IEEE Transactions on Information Technology in Biomedicine,Vol 15, pp. 324-333
Rawte, V., & Roy, B. (2015, June). Thyroid Disease Diagnosis using Ontology based Expert System. In International Journal of Engineering Research and Technology (Vol. 4, No. 06, June-2015). IJERT
Silber, D. (2003). The case for eHealth. Maastricht, The Netherlands: European Institute of Public Administration.
Smith, P. (2005, April). A Comprehensive Look at Hormones and the Effects of Hormone Replacement. In 14th Annual International Congress on Anti-Aging Medicine, Orlando, Fla. Retrieved June (Vol. 5, p. 2015)
Woo, Y. S., Bahk, W. M., Hong, J., Yoon, B. H., Hwang, T. Y., Kim, M. D., and Jon, D. I. (2016). Use of a Smartphone Application to Screen for Bipolar Spectrum Disorder in a Community Sample. Health informatics journal, Vol. 22, pp. 779-788
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