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Ontology-Based Decision Support Systems for Health Data Management to Support Collaboration in Ambient Assisted Living and Work Reintegration

Abstract : The modern evolution of healthcare systems towards even more complex networks has highlighted the emerging need of a standardized and interoperable model for the management of health data. Several studies in the past years have underlined how the adoption of Semantic Web technologies can provide a valuable solution for both of the aforementioned needs. Semantic modelling of health-data can indeed provide a sound and sharable conceptualization of a patient’s health condition and can leverage automatic generation of new knowledge related to the clinical contexts. In fact, thanks to reasoning processes these technologies can be used as part of decision-support systems in a variety of domains. In this paper two examples of ontologies are presented. Both models rely on a worldwide-known classification and are the basis for two decision-support tools related to the Ambient Assisted Living and Work Reintegration domains, which enable cooperation among different clinical and non-clinical stakeholders.
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Daniele Spoladore. Ontology-Based Decision Support Systems for Health Data Management to Support Collaboration in Ambient Assisted Living and Work Reintegration. 18th Working Conference on Virtual Enterprises (PROVE), Sep 2017, Vicenza, Italy. pp.341-352, ⟨10.1007/978-3-319-65151-4_32⟩. ⟨hal-01674911⟩

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