Fuzzy Mamdani Model of Diagnostics of Infectious Diseases in Cows

This article examines the issue of ensuring high-quality diagnostics in veterinary medicine through the use of artificial intelligence knowledge bases. It is shown that intelligent systems facilitate the accumulation, structuring, and dissemination of professional knowledge among specialists, provide access to expert information, and improve decision-making efficiency in veterinary practice. The main focus is on the development of a Mamdani fuzzy logic model designed for the diagnosis of infectious diseases in cattle. The proposed approach helps improve diagnostic accuracy, optimize clinical data analysis processes, and support specialists in making well-grounded veterinary decisions. The results demonstrate the strong potential of artificial intelligence methods for improving the quality of veterinary and medical care.