Artificial intelligence is beginning to create value for selected small animal veterinary applications while...

Area of Science:

• Veterinary Medicine
• Artificial Intelligence
• Data Science

Background:

• Artificial intelligence (AI) presents a powerful opportunity to enhance veterinary practice.
• Effective AI implementation necessitates solutions targeting specific challenges faced by veterinarians.
• The integration of AI in veterinary medicine is rapidly evolving.

Purpose of the Study:

• To review current applications of AI in small animal veterinary medicine.
• To assess the tangible value and limitations of AI across different use cases.
• To identify key factors influencing the successful deployment of AI in veterinary settings.

Main Methods:

• Review of four key AI use cases in small animal veterinary medicine: image analysis, early disease detection, administration support, and disease surveillance.
• Presentation of the current technological status and available AI tools for each use case.
• Analysis of value creation and data-related limitations.

Main Results:

• Tangible value creation from AI applications in veterinary medicine is inconsistent across different use cases.
• AI applications show promise in image analysis, disease detection, administration, and surveillance.
• The availability and quality of data, particularly electronic health records, significantly impact AI effectiveness.

Conclusions:

• AI holds considerable potential to support veterinarians, but its practical impact varies.
• Addressing data accessibility and quality is crucial for unlocking AI's full potential in veterinary medicine.
• Further development and validation of AI tools are needed for specific veterinary pain points.