Decision Support Systems for Intensive Medicine

Based on Knowledge Discovery in Database


Abstract

 

This master dissertation entitled “Decision Support System for Intensive Medicine based on the Knowledge Discovery in Databases” is in the Intelligent Information Systems area for intensive medicine and sets out to demonstrate a critical reflection about the state of the art, to present the information system architecture and all of work that had developed with the objective to create one Intelligent Decision Support System (IDSS) for Intensive Medicine. The surfacing of intensive care, can aid the possibility of the recovery of dying patients or patients in organ failure state. This recovery depends largely on the decisions that are taken in the Intensive Care Units, because these may influence more the outcome than any other innovative intervention. In this context it is important that all necessary information for the decision process is in electronic format. This work is part of Research Project called INTCare and the work done in the past is the base for the construction of the IDSS. In order to obtain all necessary information, as defined previously, it was essential the modeling of the architecture of information systems so that this would enable the collection and storage of data in real time and online mode The need to find a solution for the collection of vital signs and to store the recurring data recorded in paper format, such as the sheet of Nursing, induced the analyses of similar systems. Important factors for the decision process were also defined and demonstrated to be essential for the development of the information model for this system In this document it is possible to ascertain the progress that has been observed in Intensive Care for IDSS and the way of data was collected. One of these systems is the INTCare that, through its various agents, allows monitoring and data acquisition in real-time data which, through Artificial Intelligence techniques is transformed into knowledge, thus allowing the construction of predicting and decision models that will be integrated into Intelligent Decision Support System.