Variables characterization by using computing intelligence to identify the cattle s health disorders

Detecting disorders in lab tests applied in animals is a complex process that implies linking different variables and clinical factors of the individuals. lt is why during the development of the present research, some computing intelligence techniqueswere evaluated, which contributed to the behavior...

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Main Authors: Sarmiento-Pacanchique, Edgar Leonardo, Torres-Corredor, Oscar Iván, Ballesteros-Ricaurte, Javier Antonio, Cáceres-Castellanos, Gustavo
Format: Online
Language:spa
Published: Universidad Pedagógica y Tecnológica de Colombia 2015
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Online Access:https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4112
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author Sarmiento-Pacanchique, Edgar Leonardo
Torres-Corredor, Oscar Iván
Ballesteros-Ricaurte, Javier Antonio
Cáceres-Castellanos, Gustavo
author_facet Sarmiento-Pacanchique, Edgar Leonardo
Torres-Corredor, Oscar Iván
Ballesteros-Ricaurte, Javier Antonio
Cáceres-Castellanos, Gustavo
author_sort Sarmiento-Pacanchique, Edgar Leonardo
collection OJS
description Detecting disorders in lab tests applied in animals is a complex process that implies linking different variables and clinical factors of the individuals. lt is why during the development of the present research, some computing intelligence techniqueswere evaluated, which contributed to the behavior patterns identification of the most important disorders detected in CBC tests applied in cattle, Although several computing intelligence algorithms are used in medical troubleshooting, no record of researches in veterinary medical processes was found. Once the thorough characterization of the variables and the evaluation of the computing intelligence techniques were made, it was determined that the algorithm that best fits to the purpose of the proposed data analysis is FP-Growth.
format Online
id oai:oai.revistas.uptc.edu.co:article-4112
institution Revista Ciencia y Agricultura
language spa
publishDate 2015
publisher Universidad Pedagógica y Tecnológica de Colombia
record_format ojs
spelling oai:oai.revistas.uptc.edu.co:article-41122018-11-21T00:12:47Z Variables characterization by using computing intelligence to identify the cattle s health disorders Caracterización de variables utilizando inteligencia computacional para identificar alteraciones en la salud de bovinos Sarmiento-Pacanchique, Edgar Leonardo Torres-Corredor, Oscar Iván Ballesteros-Ricaurte, Javier Antonio Cáceres-Castellanos, Gustavo data analysis algorithms animal health FP—growth. Análisis de datos Algoritmos Sanidad animal FP-Growth Detecting disorders in lab tests applied in animals is a complex process that implies linking different variables and clinical factors of the individuals. lt is why during the development of the present research, some computing intelligence techniqueswere evaluated, which contributed to the behavior patterns identification of the most important disorders detected in CBC tests applied in cattle, Although several computing intelligence algorithms are used in medical troubleshooting, no record of researches in veterinary medical processes was found. Once the thorough characterization of the variables and the evaluation of the computing intelligence techniques were made, it was determined that the algorithm that best fits to the purpose of the proposed data analysis is FP-Growth. La detección de alteraciones de la salud de los animales mediante pruebas de laboratorio es un proceso complejo que implica relacionar diversas variables y factores clínicos de los individuos, por ello, en esta investigación se evaluaron técnicas de inteligencia computacional que contribuyeron a la identificación de patrones de comportamiento de las alteraciones detectadas en las pruebas de hemograma aplicadas en bovinos. Aunque diversos algoritmos de inteligencia computacional son utilizados en la solución de problemas médicos, no se encontró registro de investigaciones en procesos médicos veterinarios. Una vez hecha una minuciosa caracterización de las variables y la evaluación de las técnicas de inteligencia computacional, se determinó que el algoritmo que mejor se ajusta al propósito de análisis de datos planteado es FP-Growth. Universidad Pedagógica y Tecnológica de Colombia 2015-01-19 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion investigation application/pdf https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4112 10.19053/01228420.4112 Ciencia y Agricultura; Vol. 12 No. 1 (2015); 39-47 Ciencia y Agricultura; Vol. 12 Núm. 1 (2015); 39-47 2539-0899 spa https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4112/3558 Copyright (c) 2015 CIENCIA Y AGRICULTURA
spellingShingle data analysis
algorithms
animal health
FP—growth.
Análisis de datos
Algoritmos
Sanidad animal
FP-Growth
Sarmiento-Pacanchique, Edgar Leonardo
Torres-Corredor, Oscar Iván
Ballesteros-Ricaurte, Javier Antonio
Cáceres-Castellanos, Gustavo
Variables characterization by using computing intelligence to identify the cattle s health disorders
title Variables characterization by using computing intelligence to identify the cattle s health disorders
title_alt Caracterización de variables utilizando inteligencia computacional para identificar alteraciones en la salud de bovinos
title_full Variables characterization by using computing intelligence to identify the cattle s health disorders
title_fullStr Variables characterization by using computing intelligence to identify the cattle s health disorders
title_full_unstemmed Variables characterization by using computing intelligence to identify the cattle s health disorders
title_short Variables characterization by using computing intelligence to identify the cattle s health disorders
title_sort variables characterization by using computing intelligence to identify the cattle s health disorders
topic data analysis
algorithms
animal health
FP—growth.
Análisis de datos
Algoritmos
Sanidad animal
FP-Growth
topic_facet data analysis
algorithms
animal health
FP—growth.
Análisis de datos
Algoritmos
Sanidad animal
FP-Growth
url https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4112
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