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Formalizing and Leveraging Domain Knowledge in the K4CARE Home Care Platform
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Author(s): Ákos Hajnal (Computer and Automation Research Institute of the Hungarian Academy of Sciences, Hungary), Antonio Moreno (University Rovira i Virgili, Spain), Gianfranco Pedone (Computer and Automation Research Institute of the Hungarian Academy of Sciences, Hungary), David Riaño (University Rovira i Virgili, Spain)and László Zsolt Varga (Computer and Automation Research Institute of the Hungarian Academy of Sciences, Hungary)
Copyright: 2009
Pages: 24
Source title:
Semantic Knowledge Management: An Ontology-Based Framework
Source Author(s)/Editor(s): Antonio Zilli (University of Salento, Italy), Ernesto Damiani (University of Milan, Italy), Paolo Ceravolo (University of Milan, Italy), Angelo Corallo (University of Salento, Italy)and Gianluca Elia (University of Salento, Italy)
DOI: 10.4018/978-1-60566-034-9.ch013
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Abstract
This chapter proposes an agent-based architecture for home care support, whose main capability is to continuously admit and apply new medical knowledge entered into the system, capturing and codifying implicit knowledge deriving from the medical staff. Knowledge is the fundamental catalyst in all application domains, and this is particularly true especially for the medical context. Knowledge formalization, representation, exploitation, creation, and sharing are some of the most complex issues related to Knowledge Management. Moreover, Artificial Intelligence techniques and MAS (Multi-Agent System) in health care are increasingly justifying the large demand for their application, since traditional techniques are often not suitable to manage complex tasks or to adapt to unexpected events. The chapter presents also a methodology for approaching medical knowledge management from its representation symbolism to the implementation details. The codification of health care treatments, as well as the formalization of domain knowledge, serves as an explicit, a priori asset for the agent platform implementation. The system has the capability of applying new, implicit knowledge emerging from physicians.
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