Modularising ontology and designing inference patterns to personalise health condition assessment: the case of obesity

Journal of Biomedical Semantics
Aleksandra SojicMarco Sacco

Abstract

The public health initiatives for obesity prevention are increasingly exploiting the advantages of smart technologies that can register various kinds of data related to physical, physiological, and behavioural conditions. Since individual features and habits vary among people, the design of appropriate intervention strategies for motivating changes in behavioural patterns towards a healthy lifestyle requires the interpretation and integration of collected information, while considering individual profiles in a personalised manner. The ontology-based modelling is recognised as a promising approach in facing the interoperability and integration of heterogeneous information related to characterisation of personal profiles. The presented ontology captures individual profiles across several obesity-related knowledge-domains structured into dedicated modules in order to support inference about health condition, physical features, behavioural habits associated with a person, and relevant changes over time. The modularisation strategy is designed to facilitate ontology development, maintenance, and reuse. The domain-specific modules formalised in the Web Ontology Language (OWL) integrate the domain-specific sets of rules formalised in ...Continue Reading

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Citations

Feb 8, 2018·Journal of Biomedical Semantics·Shaker El-SappaghKyung-Sup Kwak

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Software Mentioned

OntoGUI Manager
PhysicalStatus RBox
SWRL
Stardog
PhysiologicalStatus
Common
OWL
OntoClean
Pellet
PEGASO

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