Role of Artificial Intelligence in Disease Diagnostics in Veterinary Medicine

Dear Colleagues,

The development of artificial intelligence (AI) tools in veterinary medicine has taken off rapidly in the last few years. AI systems and tools are being designed and developed for a wide range of applications, such as (1) disease diagnostics at the individual animal level, e.g., hip dysplasia in dogs, and at the group level, e.g., cough detection as an indicator of respiratory disease in a fattening pig stable, (2) production optimization, e.g., improving milk yield and reproductive performance in dairy cows, (3) animal welfare monitoring, e.g., stress detection in chicken broods, and (4) disease outbreak prediction at a regional level, e.g., early detection of avian influenza. Research in these AI systems and tools spans both companion animals, e.g., cats, dogs, and horses, as well as production animals, e.g., chickens, pigs, and cows.  

Despite the growing research interest in AI applications in veterinary medicine, the adoption of AI tools in routine veterinary practice is uncommon to non-existent. A key barrier is the lack of trust and interpretability of AI systems, particularly when deployed in real-world settings that differ from the data on which they were trained. In practice, veterinary data are often heterogeneous, noisy, and subject to distributional shifts (e.g., across farms, devices, or populations), making robust generalization a critical challenge. Moreover, current AI systems often fail to adequately quantify uncertainty, limiting their reliability in high-stakes clinical decision-making.

This Special Issue therefore aims to bring AI tools relevant for veterinary medicine closer to the general practitioner. Topics of interest include, but are not limited to, AI-assisted diagnosis and imaging, disease prediction, and condition monitoring, which are based on AI methods for individual animal care. We particularly encourage research with clear clinical significance, innovative methods, and translational value. By combining advances in AI and computation with veterinary medicine, this Special Issue aims to promote more advanced, accurate, transparent, generalizable, and truly actionable diagnostic solutions for real-world veterinary practice and animal health.

Prof. Dr. Luc Duchateau
Prof. Dr. Sofie Van Hoecke
Guest Editors

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• artificial intelligence
• veterinary diagnostics
• medical imaging
• condition monitoring
• machine learning
• digital pathology
• animal health monitoring
• trustworthy AI