Artificial Intelligence in Veterinary Medicine: From Data to Clinical Decision-Making

Artificial intelligence (AI) is rapidly transforming veterinary medicine, creating new opportunities to enhance disease diagnosis, monitoring, and treatment. The review explores current AI applications in veterinary practice and their expanding role in diagnostic procedures, health management, prognostics and treatment planning in clinical settings. AI provides veterinarians with the tools to recognize complex patterns that human could easily miss through machine learning, deep learning and multimodal data analysis which leads to improved therapeutic outcomes and enhanced animal welfare. AI implementation in veterinary medicine continues to encounter multiple obstacles which prevent its widespread adoption in veterinary practice. Because of limited access to large and high-quality datasets, as well as ongoing concerns regarding bias, transparency, and infrastructure, its full potential has yet to be realized. Looking ahead, multimodal AI approaches hold significant promise for advancing individualized animal healthcare. Achieving this goal will require collaboration between veterinarians, data scientists, and policymakers, along with sustained investment in education, research, and technology infrastructure. Together, these initiatives will promote the safe and practical introduction of AI to veterinary medicine.

کلیدواژه ها:

Artificial intelligence ، Multimodal diagnostics ، Veterinary medicine ، Machine learning ، Predictive models