2009
Santos, M. F.; Portela, F.; Vilas-Boas, M.; Machado, J.; Abelha, A.; Neves, J.; Silva, A.; Rua, F.
Information architecture for intelligent decision support in intensive medicine Journal Article
Em: WSEAS Transactions on Computers, vol. 8, não 5, pp. 810-819, 2009, ISSN: 11092750, (cited By 18).
Resumo | Links | BibTeX | Etiquetas: Architectural design; Artificial intelligence; Database systems; Decision support systems; Decision theory; Information retrieval; Information science; Intensive care units; Knowledge management; Mergers and acquisitions; Real time systems, Decision making, Information models; INTCare; Intelligent decision support systems; Intensive care; Knowledge discovery in databases; Real-time data acquisition
@article{Santos2009810,
title = {Information architecture for intelligent decision support in intensive medicine},
author = {M. F. Santos and F. Portela and M. Vilas-Boas and J. Machado and A. Abelha and J. Neves and A. Silva and F. Rua},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-69549098007&partnerID=40&md5=eadb2fee9457fd205183fd9b3262ce5b},
issn = {11092750},
year = {2009},
date = {2009-01-01},
journal = {WSEAS Transactions on Computers},
volume = {8},
number = {5},
pages = {810-819},
abstract = {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.},
note = {cited By 18},
keywords = {Architectural design; Artificial intelligence; Database systems; Decision support systems; Decision theory; Information retrieval; Information science; Intensive care units; Knowledge management; Mergers and acquisitions; Real time systems, Decision making, Information models; INTCare; Intelligent decision support systems; Intensive care; Knowledge discovery in databases; Real-time data acquisition},
pubstate = {published},
tppubtype = {article}
}
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.