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Resurgery Clusters in Intensive Medicine?

The field of critical care medicine is confronted every day with cases of surgical interventions. When Data Mining is properly applied in this field, it is possible through predictive models to identify if a patient, should or should not have surgery again upon the same problem. The goal of this wor...

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Autor Principal: Mota Pinto, Filipe Jorge
Formato: Artículos
Lenguaje:it
Publicado: 2017
Materias:
CLUSTERING
DATA MINING
INTENSIVE CARE UNITS
INTCARE
RE-INTERVENTION
INTERVENTION
Acceso en línea:http://repositorio.educacionsuperior.gob.ec/handle/28000/3690
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spelling oai:localhost:28000-36902017-04-12T18:14:19Z Resurgery Clusters in Intensive Medicine? Mota Pinto, Filipe Jorge CLUSTERING DATA MINING INTENSIVE CARE UNITS INTCARE RE-INTERVENTION INTERVENTION The field of critical care medicine is confronted every day with cases of surgical interventions. When Data Mining is properly applied in this field, it is possible through predictive models to identify if a patient, should or should not have surgery again upon the same problem. The goal of this work is to apply clustering techniques in collected data in order to categorize re-interventions in intensive care. By knowing the common characteristics of the re-intervention patients it will be possible to help the physician to predict a future resurgery. For this study various attributes were used related to the patient's health problems like heart problems or organ failure. For this study it was also considered important aspects such as age and what type of surgery the patient was submitted. Classes were created with the patients? age and the number of days after the first surgery. Another class was created where the type of surgery that the patient was operated upon was identified. This study comprised Davies Bouldin values between -0.977 and -0.416. The used variables, in addition to being provided by Hospital de Santo Ant?nio in Porto, they are provided from the electronic medical record. http://www.sciencedirect.com/science/article/pii/S1877050916322177 2017-03-16T21:26:02Z 2017-03-16T21:26:02Z 2016 article Peixoto, Ricardo. et al. (2016). Resurgery Clusters in Intensive Medicine. Procedia Computer Science, Vol 98, pp. 528-533. 1877-0509 http://repositorio.educacionsuperior.gob.ec/handle/28000/3690 it openAccess http://creativecommons.org/licenses/by-nc-sa/3.0/ec/ 528-533
institution SENESCYT
collection Repositorio SENESCYT
biblioteca Biblioteca Senescyt
language it
format Artículos
topic CLUSTERING
DATA MINING
INTENSIVE CARE UNITS
INTCARE
RE-INTERVENTION
INTERVENTION
spellingShingle CLUSTERING
DATA MINING
INTENSIVE CARE UNITS
INTCARE
RE-INTERVENTION
INTERVENTION
Mota Pinto, Filipe Jorge
Resurgery Clusters in Intensive Medicine?
description The field of critical care medicine is confronted every day with cases of surgical interventions. When Data Mining is properly applied in this field, it is possible through predictive models to identify if a patient, should or should not have surgery again upon the same problem. The goal of this work is to apply clustering techniques in collected data in order to categorize re-interventions in intensive care. By knowing the common characteristics of the re-intervention patients it will be possible to help the physician to predict a future resurgery. For this study various attributes were used related to the patient's health problems like heart problems or organ failure. For this study it was also considered important aspects such as age and what type of surgery the patient was submitted. Classes were created with the patients? age and the number of days after the first surgery. Another class was created where the type of surgery that the patient was operated upon was identified. This study comprised Davies Bouldin values between -0.977 and -0.416. The used variables, in addition to being provided by Hospital de Santo Ant?nio in Porto, they are provided from the electronic medical record.
author Mota Pinto, Filipe Jorge
author_facet Mota Pinto, Filipe Jorge
author_sort Mota Pinto, Filipe Jorge
title Resurgery Clusters in Intensive Medicine?
title_short Resurgery Clusters in Intensive Medicine?
title_full Resurgery Clusters in Intensive Medicine?
title_fullStr Resurgery Clusters in Intensive Medicine?
title_full_unstemmed Resurgery Clusters in Intensive Medicine?
title_sort resurgery clusters in intensive medicine?
publishDate 2017
url http://repositorio.educacionsuperior.gob.ec/handle/28000/3690
_version_ 1634995182690631680
score 11,871979

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