Iron Value Classification in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis using Data Mining

Catarina Peixoto, Hugo Peixoto, José Machado, António Abelha, Manuel F. Santos

2018

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.

Paper Citation

in Harvard Style

Peixoto C., Peixoto H., Machado J., Abelha A. and F. Santos M. (2018). Iron Value Classification in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis using Data Mining.In - HSP, ISBN , pages 0-0. DOI: 10.5220/0006820802850290

in Bibtex Style

@conference{hsp18,
author={Catarina Peixoto and Hugo Peixoto and José Machado and António Abelha and Manuel F. Santos},
title={Iron Value Classification in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis using Data Mining},
booktitle={ - HSP,},
year={2018},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006820802850290},
isbn={},
}

in EndNote Style

TY - CONF

JO - - HSP,
TI - Iron Value Classification in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis using Data Mining
SN -
AU - Peixoto C.
AU - Peixoto H.
AU - Machado J.
AU - Abelha A.
AU - F. Santos M.
PY - 2018
SP - 0
EP - 0
DO - 10.5220/0006820802850290