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

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.

Keywords

data analysis, algorithms, animal health, FP—growth.

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References

  • J. Muñoz Pérez, Inteligencia computacional inspirada en la vida, Universidad de Málaga, España, 2011.
  • J. L. Camargo-Cuervo, E. F. Suárez-Mendoza, and J. A. Ballesteros-Ricaurte, “Comparison between Oracle BPM and JBPM in the Admission Process Optimization”, Fac. Ing. UPTC, vol. 22, no. 34, pp. 85-96, 2013.
  • A. R. Novoa, Salud animal, manejo y administración de sistemas de producción de leche. San José de Costa Rica, 1983.
  • M. Cabrera-Hernández, M. del C. Paderni-López, R. Hita Torres, A. Delgado-Ramos, M. A. Tardío-López, and D. Derivet-Thaureaux, “Aplicaciones médicas como ayuda al diagnóstico en la medicina. Experiencia SOFTEL-MINSAP”, Rev. Cuba. Informática Médica, vol. 4, no. 2, pp. 199-212, 2012.
  • P. Chausa-Fernández, E. J. Gómez-Aguilera, C. Cáceres-Taladriz, F. García-Alcaide, and J. M. Gatell-Artigas, Extracción de Reglas de Asociación en una Base de Datos Clínicos de Pacientes con Vih/Sida”, p. 4, 2006.
  • Y. Cárdenas, L. Guerra y D.Mauricio, Diseño de un algoritmo genético para la generación de conocimiento en el diagnóstico del Síndrome Autista. Facultad de Ingeniería de Sistemas e Informática Universidad Nacional Mayor de San Marcos, 2014.
  • R . C. Naranjo-Cuervo and L. M. Sierra-Martínez, “Software tool for analyzing the family shopping basket without candidate generation”, Ing. e Investig. Vol. 29, No. 1, 2010.
  • J. S. González-Sanabria and G. Cáceres-Castellanos, “Comparison of GIS desktop tools for development of SIGPOT,” Lat. Am. Trans. IEEE (Revista IEEE Am. Lat.), vol. 11, no. 1, pp. 86-90, 2013.

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