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CBR Technique in Veterinary Pathological Anatomy

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ENTERprise Information Systems (CENTERIS 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 110))

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Abstract

Veterinary Pathological Anatomy consists in the application of criteria based in the knowledge of the macroscopic and histological lesions to obtain a final pathological diagnosis. The aim of this specific diagnosis is, generally, to determine which disease affects the animal, in case of being alive, or what the cause of death in case it was death.

Unlike human medicine, dedicated to a single specie, the Veterinary Medicine is dedicated to different animal species, usually grouped into specialties based in affinity of species (e.g. pets - dogs and cats, ruminants, exotic species, etc). Also pathological anatomy uses exhaustive classifications of different types (e.g. infectious diseases, metabolic diseases, endocrine diseases, neoplasm’s, etc.). So the urgent need to compile all available information to obtain a diagnosis, in a short period of time, which will help to save the animal life, is the constant challenge placed to the professional experts in the area concerned.

The proposal of using the Case Based-Reasoning (CBR) technique in this area aims at offer a training tool to the professional and attendants, as well as a research instrument to analyze the similarities or deviations of the diagnosed cases, to improve the veterinarian pathologist’s performance and therefore achieve greater success in helping clinicians saving more animals.

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© 2010 Springer-Verlag Berlin Heidelberg

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Tomé, P., Vala, H. (2010). CBR Technique in Veterinary Pathological Anatomy. In: Quintela Varajão, J.E., Cruz-Cunha, M.M., Putnik, G.D., Trigo, A. (eds) ENTERprise Information Systems. CENTERIS 2010. Communications in Computer and Information Science, vol 110. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16419-4_41

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  • DOI: https://doi.org/10.1007/978-3-642-16419-4_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16418-7

  • Online ISBN: 978-3-642-16419-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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