Authors:
Filipe Portela
;
Filipe Pinto
and
Manuel Filipe Santos
Affiliation:
Universidade do Minho, Portugal
Keyword(s):
Data Mining, KDD, Real-time, Pervasive, Intelligent Decision Support System, Intensive Care.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Business Intelligence
;
Intelligent Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge Management Projects
;
Knowledge-Based Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
The introduction of an Intelligent Decision Support System (IDSS) in a critical area like the Intensive Medicine is a complex and difficult process. In this area, their professionals don’t have much time to document the cases, because the patient direct care is always first. With the objective to reduce significantly the manual records and, enabling, at the same time, the possibility of developing an IDSS which can help in the decision making process, all data acquisition process and knowledge discovery in database phases were automated. From the data acquisition to the knowledge discovering, the entire process is autonomous and executed in real-time. On-line induced data mining models were used to predict organ failure and outcome. Preliminary results obtained with a limited population of patients showed that this approach can be applied successfully.