Authors:
Sara Colantonio
1
;
Massimo Martinelli
1
;
Ovidio Salvetti
1
;
Giuseppe De Pietro
2
;
Massimo Esposito
2
and
Alberto Machì
2
Affiliations:
1
ISTI-CNR, Italy
;
2
ICAR-CNR, Italy
Keyword(s):
Decision support, Knowledge formalization, Ontologies.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Decision Support Systems
;
Enterprise Information Systems
;
Expert Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
Due to the current socio-economic impact of chronic diseases, a strong effort is being spent in the development of ICT applications able to support a new care paradigm specialized for chronic patients. Such applications are mainly based on patients’ telemonitoring for the collection of a number of relevant physiological parameters aimed at identifying and preventing acute events, while maximizing patients’ quality of life and reducing clinical costs. The most advanced and challenging features of these ICT applications are intelligent services devoted to the interpretation of monitored patients’ data for supporting clinicians in their routine management of chronic patients. In this paper, a Knowledge-based Clinical Decision Support System (KB-CDSS) is presented, which is aimed at aiding clinical professionals in managing chronic patients on a daily basis, by assessing their current status, helping face their worsening conditions, and preventing disease exacerbation events. The CDSS ha
s been developed by encoding the relevant knowledge elicited from clinicians who have a large experience in patients’ monitoring. A formalism based on ontologies and rules was selected to build the Knowledge Base according to a scenario-based approach. The system is currently under validation for the management of real clinical cases.
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