Abstract—In veterinary medicine, artificial intelligence (AI) is making its mark. It is improving the efficiency and accuracy of diagnosis, clinical operations and animal health. It is used in diagnostic imaging, disease prediction, behavior monitoring and decision support system are widespread. The use of deep learning models particularly in complex neural networks in diagnostic imaging to detect anomalies of radiographs and other scanning of animals like dog, cat, livestock etc. These tools help veterinarians interpret faster with more accurate diagnoses. AI models that are trained on a number of epidemiological datasets can predict outbreaks of disease and in turn, disease management. An additional important area for the implementation of AI consists in monitoring animal behavior and welfare. Mobile apps and computer vision techniques powered by AI can detect facial expressions, movement patterns indicative of pain, distress, or illness. As a result, it is especially important for farm animals and companion animals to improve their welfare and clinical outcomes. AI clinical decision support systems (CDSS) offer real time diagnosis and treatment advice and improve efficiency and lessen human error. Today’s veterinary clinics increasingly find these systems indispensable tools.It is especially useful in emergencies or complex complications. Still, various challenges remain in the way such as data quality, algorithm transparency, and ethical use of AI. Veterinary profession should also be trained on new technologies like the rest of the society. Keywords—Artificial intelligence, Veterinary care, Machine Learning, Disease Prediction, Animal Behavior Monitoring ,Livestock Health Management, Real-time Monitoring, Smart Veterinary Tools
Prakruthi et al. (Tue,) studied this question.
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