2016
Coimbra, A.; Vicente, H.; Abelha, A.; Santos, M. Filipe; Machado, J.; Neves, J.; Neves, J.
Prediction of length of hospital stay in preterm infants a case-based reasoning view Proceedings Article
Em: L.C., Czarnowski I. Howlett R. J. Jain (Ed.): pp. 115-128, Springer Science and Business Media Deutschland GmbH, 2016, ISSN: 21903018, (cited By 1; Conference of 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 ; Conference Date: 15 June 2016 Through 17 June 2016; Conference Code:177269).
Resumo | Links | BibTeX | Etiquetas: Artificial intelligence; Case based reasoning; Computation theory; Computer circuits; Decision support systems; Knowledge representation; Logic programming; Program diagnostics; Quality of service; Reconfigurable hardware, Diagnosis decision; Healthcare facility; Knowledge representation and reasoning; Length of hospital stays; Length of stay; Neonatology; Overall accuracies; Preterm infants, Problem solving
@inproceedings{Coimbra2016115,
title = {Prediction of length of hospital stay in preterm infants a case-based reasoning view},
author = {A. Coimbra and H. Vicente and A. Abelha and M. Filipe Santos and J. Machado and J. Neves and J. Neves},
editor = {Czarnowski I. Howlett R.J. Jain L.C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977097691&doi=10.1007%2f978-3-319-39630-9_10&partnerID=40&md5=6289feafb914ab92696ef065ab6419ed},
doi = {10.1007/978-3-319-39630-9_10},
issn = {21903018},
year = {2016},
date = {2016-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {56},
pages = {115-128},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory information. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9 %) and by reducing the computational time with values around 21.3 %. © Springer International Publishing Switzerland 2016.},
note = {cited By 1; Conference of 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 ; Conference Date: 15 June 2016 Through 17 June 2016; Conference Code:177269},
keywords = {Artificial intelligence; Case based reasoning; Computation theory; Computer circuits; Decision support systems; Knowledge representation; Logic programming; Program diagnostics; Quality of service; Reconfigurable hardware, Diagnosis decision; Healthcare facility; Knowledge representation and reasoning; Length of hospital stays; Length of stay; Neonatology; Overall accuracies; Preterm infants, Problem solving},
pubstate = {published},
tppubtype = {inproceedings}
}