@inproceedings{963210646c064ad2a7b8a84789e36751,
title = "Analysis of cardiorespiratory interaction in patients submitted to the T-tube test in the weaning process implementing symbolic dynamics and neural networks",
abstract = "The determination of the optimal time of the patients in weaning trial process from Mechanical Ventilation (MV), between patients capable of maintaining spontaneous breathing and patients that fail to maintain spontaneous breathing, is a very important task in intensive care unit. Symbolic Dynamic (SD) and Neural Networks (NN) techniques were applied in order to develop a classifier for the study of patients on weaning trial process. The respiratory pattern of each patient was characterized through different time series. In order to reduce the dimensionality of the system Forward Selection is implemented, obtaining a classification performance result of 85,96 ±6,26% with 64 variables differentiating between 3 classes analyzed at same time.",
keywords = "Neural networks, Signal processing, Wean DB, Weaning trials",
author = "Arizmendi, {C. J.} and Solano, {E. H.} and H. Gonzalez and Acuna, {H. Gonzalez} and Giraldo, {B. F.}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018 ; Conference date: 26-05-2018 Through 28-05-2018",
year = "2018",
month = jun,
day = "25",
doi = "10.1109/ICAIBD.2018.8396175",
language = "Ingl{\'e}s",
series = "2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "101--105",
booktitle = "2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018",
}