loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Filipe Portela ; Filipe Pinto and Manuel Filipe Santos

Affiliation: Universidade do Minho, Portugal

ISBN: 978-989-8565-31-0

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.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.172.195.49

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Portela, F.; Pinto, F. and Santos, M. (2012). Data Mining Predictive Models for Pervasive Intelligent Decision Support in Intensive Care Medicine.In Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2012) ISBN 978-989-8565-31-0, pages 81-88. DOI: 10.5220/0004141500810088

@conference{kmis12,
author={Filipe Portela. and Filipe Pinto. and Manuel Filipe Santos.},
title={Data Mining Predictive Models for Pervasive Intelligent Decision Support in Intensive Care Medicine},
booktitle={Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2012)},
year={2012},
pages={81-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004141500810088},
isbn={978-989-8565-31-0},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2012)
TI - Data Mining Predictive Models for Pervasive Intelligent Decision Support in Intensive Care Medicine
SN - 978-989-8565-31-0
AU - Portela, F.
AU - Pinto, F.
AU - Santos, M.
PY - 2012
SP - 81
EP - 88
DO - 10.5220/0004141500810088

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.