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Abstracts

XVII conference

Diagnostic expert support system for veterinary medicine

Zueva G., Karp V.

Moscow State Institute of Radio Engineering, Electronics and Automatics (Technical University), Cybernetics department, Information Technology subdepartment Vernadskogo avenue 78, Moscow, Russia (The Russian Federation) Tel.: +7(962) 929 51 21, Postal code: 119454 E-mail: zzzlost@gmail.com

1 pp. (accepted)

Animals are amenable to a great variety of diseases. Therefore in order to identify a case veterinarians have to take into account a whole number of various factors relying both on their personal experience and materials being published in scientific journals and reference books. Frequently, constant growth of information volumes significantly perplexes the process of data analysis and diagnosing in each particular case. [1]

“Veterinary surgeon” is an expert support system (ESS) being currently developed for veterinary medicine in order to increase domestic animals diagnosing efficiency. At the moment it is implemented by example of ESS for typical dog illnesses.

An appropriate knowledge base is generated for several classes of illnesses, such as eye troubles; skin troubles; ear troubles and locomotor system troubles. Multipurpose input algorithm is also created.

The basic idea of this algorithm is the following: all symptoms which were chosen by user are compared with the predefined sets of symptoms being peculiar to each group of diagnoses. If a symptom belongs to some particular group the match is registered and the algorithm proceeds to subgroup identification. [2].

These steps are to be recurred until all the symptoms being marked by the veterinarian are examined. Finally, illnesses must be listed in descending order by counter value and shown to the user. Preference is given to those of them which have the biggest number of “votes”.

Described expert support system has the following features:

• User-friendly input of symptoms and their further processing;

• Visual symptom description;

• Providing user with a final conclusion and a number of “votes” for each of the variants;

• Getting diagnosis substantiations written in the professional user language.

References

1. A.A. Kuzmin, Dog illnesses. Medical practitioner handbook. Harkov, 2002, p. 345.

2. G.A. Zueva, V.P. Karp “Knowledge base for electronic diagnostic system “Eye troubles differential diagnostics for dogs” in 58th STC MIREA part 1:Information technologies and systems. Computer engineering. M:MIREA, 2009, p. 180.



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