Abstract
Expert systems designed to identify diseases in cattle may use a variety of sources of information such as clinical data, signs of disease, medical history, laboratory results, environmental exposure and other relevant factors. They can be developed based on rules, heuristics, or machine learning, using a large amount of data to train the model. The expert system may provide the veterinarian with a list of possible diagnoses, ranked by probability, based on the data provided. She may also recommend further investigations or tests for a more accurate diagnosis. The developed expert system for veterinary medicine provides a wide range of functions and capabilities to support the work of veterinarians and processing data on the incidence of cattle.
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