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...
| Main Authors: | , , , |
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| Format: | Online |
| Language: | spa |
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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 |
| _version_ | 1801706465432436736 |
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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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