Knowledge discovery in databases: an overview
AI Magazine
On agent-based software engineering
Artificial Intelligence
Decision Support Systems and Intelligent Systems
Decision Support Systems and Intelligent Systems
Adaptive Business Intelligence
Adaptive Business Intelligence
Mining data from intensive care patients
Advanced Engineering Informatics
Health data management in the medical arena
AIC'04 Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications
Journal of Medical Systems
Adaptive decision support for intensive care
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
New standards for competitive distinctions: a practical model
WSEAS Transactions on Computers
An intelligent patient monitoring system
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
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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. Furthermore, the models should be continuously assessed and optimized, if necessary, to maintain a certain accuracy. In this paper we propose an information architecture to support an adjustment to the INTCare system, an intelligent decision support system for intensive medicine. We focus on the automatization of data acquisition avoiding human intervention, describing its steps and some requirements.