Next Generation Artificial Intelligence in Veterinary Surgery: A Review of Applications, Challenges, and Patient Health Improvement

The integration of artificial intelligence (AI) into veterinary surgery is emerging as a transformative force, yet it remains in early stages compared to human medicine. Veterinary surgery faces unique challenges including species diversity, anatomical variations, limited access to advanced imaging, and a shortage of specialized surgeons. AI offers promising applications across the surgical continuum: preoperative image analysis and risk prediction, intraoperative robotic assistance and intelligent monitoring, and postoperative complication detection using wearable sensors and natural language processing. However, several critical obstacles hinder clinical adoption. These include the scarcity of large, annotated multi-species datasets, poor model generalizability due to domain shift, high infrastructure costs, unresolved legal liability for AI-related errors, and a lack of rigorous prospective trials demonstrating improved patient-centered outcomes such as survival or quality of life. Currently, AI should be viewed as an adjunct rather than a standard of care. This review critically evaluates current applications, challenges, and evidence, concluding that while AI holds considerable potential, widespread implementation requires collaborative data sharing, regulatory frameworks, veterinary-specific ethical guidelines, and randomized controlled trials focused on tangible patient benefits.

کلیدواژه ها:

Artificial Intelligence ، Veterinary Surgery ، Machine Learning