2018
Peixoto, C.; Peixoto, H.; Machado, J.; Abelha, A.; Santos, M. F.
Iron value classification in patients undergoing continuous ambulatory peritoneal dialysis using data mining Proceedings Article
Em: P.D., Ziefle M. Bamidis P. D. Bamidis (Ed.): pp. 285-290, SciTePress, 2018, ISBN: 9789897582998, (cited By 1; Conference of 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2018 ; Conference Date: 22 March 2018 Through 23 March 2018; Conference Code:135921).
Resumo | Links | BibTeX | Etiquetas: Blood analysis; Classification algorithm; Data set; False positive; Low rates; Mining classification; Peritoneal dialysis; Weka, Classification (of information), Data mining; Dialysis; Iron; Patient treatment; Software testing; Statistical tests
@inproceedings{Peixoto2018285,
title = {Iron value classification in patients undergoing continuous ambulatory peritoneal dialysis using data mining},
author = {C. Peixoto and H. Peixoto and J. Machado and A. Abelha and M. F. Santos},
editor = {Ziefle M. Bamidis P.D. Bamidis P.D.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052307397&doi=10.5220%2f0006820802850290&partnerID=40&md5=16d6619af21cc9be3469325ea0022e96},
doi = {10.5220/0006820802850290},
isbn = {9789897582998},
year = {2018},
date = {2018-01-01},
journal = {ICT4AWE 2018 - Proceedings of the 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health},
volume = {2018-March},
pages = {285-290},
publisher = {SciTePress},
abstract = {In this article, Data Mining classification techniques are employed, in order to classify as normal or not-normal the iron values from a patients’ blood analysis. The dataset used is relative to patients that were subjected to Continuous Ambulatory Peritoneal Dialysis (CAPD) treatment. Weka software was used for testing several classification algorithms into such data set. The main purpose is finding the best suitable classification algorithm, with a pleasing performance in classifying the instances of the data, whereas preserving low rate of false positives. The IBk algorithm achieved the best performance, being able to correctly classify 97.39% of the instances. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.},
note = {cited By 1; Conference of 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2018 ; Conference Date: 22 March 2018 Through 23 March 2018; Conference Code:135921},
keywords = {Blood analysis; Classification algorithm; Data set; False positive; Low rates; Mining classification; Peritoneal dialysis; Weka, Classification (of information), Data mining; Dialysis; Iron; Patient treatment; Software testing; Statistical tests},
pubstate = {published},
tppubtype = {inproceedings}
}