Authors:
Filipe Portela
1
;
Manuel Santos
1
;
Marta Vilas Boas
1
;
Fernando Rua
2
;
Álvaro Silva
2
and
José Neves
1
Affiliations:
1
University of Minho, Portugal
;
2
Hospital de Santo António, Portugal
Keyword(s):
Real-time, Knowledge Discovery in Databases, Intensive Care, INTCare, Intelligent Decision Support Systems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Collaboration and e-Services
;
Complex Systems Modeling and Simulation
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Health Information Systems
;
Integration/Interoperability
;
Intelligent Information Systems
;
Interoperability
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Simulation and Modeling
;
Software Agents and Internet Computing
;
Software and Architectures
;
Symbolic Systems
Abstract:
Daily, a great amount of data that is gathered in intensive care units, which makes intensive medicine a very attractive field for applying knowledge discovery in databases. Previously unknown knowledge can be extracted from that data in order to create prediction and decision models. The challenge is to perform those tasks in real-time, in order to assist the doctors in the decision making process. The Data Mining models should be continuously assessed and optimized, if necessary, to maintain a certain accuracy. In this paper we present the INTCare system, an intelligent decision support system for intensive medicine and the way it was adapted to the new requirements. Some preliminary results are analysed and discussed.