Real-Time Decision Support in Intensive Medicine: An intelligent approach for monitoring Data Quality

Abstract

Intensive Medicine is an area where big amounts of data are generated every day. The process to obtain knowledge from these data is extremely difficult and sometimes dangerous. The main obstacles of this process are the number of data collected manually and the quality of the data collected automatically. Information quality is a major constrain to the success of Intelligent Decision Support Systems (IDSS). This is the case of INTCare an IDSS which operates in real-time. Data quality needs to be ensured in a continuous way. The quality must be assured essentially in the data acquisition process and in the evaluation of the results obtained from data mining models. To automate this process a set of intelligent agents have been developed to perform a set of data quality tasks. This paper explores the data quality issues in IDSS and presents an intelligent approach for monitoring the data quality in INTCare system.  Index Terms-intensive care; data quality, real-time; intelligent decision support; intcare.

Improving Quality of Services in Maternity Care Triage System

“…The creation of an IDSS was inspired in an INTCare project, which is used in the Intensive Care Unit, for predicting outcomes and organ failure in patients admitted to the unit (Portela, Gago, Santos, Silva, & Rua, 2011). In GO area was followed a similar approach to this, where the system uses induced models through data mining techniques and a set of software agents to perform tasks autonomously.…”