Rethinking Radiology: Where AI Ends and the Vet Begins
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Modern Veterinary Podcast - Episode 37 - Featuring Eric Goldman, President of Vetology Innovations.
In this episode, Eric Goldman joins Jack Peploe to explore how AI can responsibly enhance veterinary diagnostics by supporting clinical expertise, improving workflow efficiency, and promoting ethical, transparent use in practice.
In this week’s episode:
- AI Is a Screening Tool – Not a Diagnosis
AI in veterinary practice should be treated as a preliminary aid, not a definitive diagnostic. It lacks access to clinical signs, history, and lab work – so final decisions must always rest with the vet’s training and clinical judgment. Technology supports, but doesn’t substitute, expertise. - Smarter Questions, Better Outcomes
By narrowing down the clinical question before consulting a specialist, AI can streamline workflows and reduce unnecessary diagnostics. For example, if AI highlights a potential intestinal obstruction, it helps focus the follow-up conversation and action plan – saving time and money. - Fit the Tool to the Vet, Not the Other Way Around
AI isn’t right for everyone. Its value depends on the vet’s comfort level with interpreting diagnostics. Practices should use AI where it enhances confidence – not where it creates confusion or increases reliance. - Ethical AI Demands Transparency
AI systems must be transparent about how data is used and how reliable results are. Independent validation, published accuracy metrics, and collaborative development with radiologists ensure responsible, ethical use in practice.
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