Abstract
This chapter describes the design of an ontology that aims to support a monitoring system for schistosomiasis. On one hand, a domain ontology for the schistosomiasis is built to support communication and collaborative work between domain experts along the monitoring steps. The domain ontology also supports data and application integration and allows some reasoning capabilities. On the other hand, a process ontology of the schistosomiasis spreading is built for explanations and decision-making. Furthermore, the possibilities of using this process ontology for prediction are also worth considering. Here, we have focused on the design of the process ontology of infectious disease spreading and its extension to schistosomiasis. We aim to provide a formal theory in the health domain to conceptualize the processes of the infectious disease spreading and to present reasoning capabilities on the disease occurrences within a population. We emphasize on the basic entities and their relations within the complex process of infectious disease spreading. A multi-level analysis of the global dynamics is provided, taking into account biomedical, clinical and epidemiological dependences. We then propose a formalization of the infectious disease spreading process. Finally, we extend the process ontology for schistosomiasis spreading in Senegal.
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Notes
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Cyc, DDPO, oXPDL, m3po et m3pl, PSL, etc.
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The PSL was developed at the National Institute of Standards and Technology (NIST), and is approved as an international standard in the document ISO 18629.
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- 4.
Recommendations "ethics and best practices in epidemiology", 1998, France.
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In epidemiology, the prevalence or prevalence proportion is the proportion of a population found to have a disease. It is arrived at by comparing the number of people found to have the disease with the total number of people studied, and is usually expressed as a fraction, as a percentage or as the number of cases per 10,000 or 100,000 people.
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Camara, G., Despres, S., Djedidi, R., Lo, M. (2014). Building a Schistosomiasis Process Ontology for an Epidemiological Monitoring System. In: Faucher, C., Jain, L. (eds) Innovations in Intelligent Machines-4. Studies in Computational Intelligence, vol 514. Springer, Cham. https://doi.org/10.1007/978-3-319-01866-9_3
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