APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN VETERINARY DIAGNOSIS AND ANIMAL MONITORING

This chapter aims to analyze the applications of Artificial Intelligence (AI) in veterinary diagnosis and animal monitoring, highlighting its impact on clinical practice and animal production systems. This is a narrative literature review based on national and international scientific publications indexed in databases such as PubMed, Scopus, and SciELO, as well as technical documents from organizations such as the World Organisation for Animal Health and the Food and Agriculture Organization of the United Nations. The findings indicate that machine learning techniques, convolutional neural networks, and big data analytics have been successfully applied to imaging interpretation, early detection of infectious diseases, outbreak prediction, and behavioral monitoring through sensors and wearable devices. The results demonstrate increased diagnostic accuracy, reduced clinical response time, and improved animal welfare. It is concluded that AI represents a strategic tool for contemporary veterinary medicine, enabling data-driven decision-making, greater production efficiency, and strengthened sanitary surveillance, although challenges remain regarding data standardization and professional training.