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

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Autores

Edgar Leonardo Sarmiento-Pacanchique
Oscar Iván Torres-Corredor
Javier Antonio Ballesteros-Ricaurte
Gustavo Cáceres-Castellanos

Abstract

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.

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Licencia de Creative Commons

All papers included in the Revista Ciencia y Agricultura are published under  Creative Commons Attribution 4.0 International

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