Artificial Intelligence-Assisted Interpretation of Veterinary Radiographs: Opportunities, Risks, and Best Practices for Clinicians.
Authors
Basran PS,Appleby R,Porter I
Affiliations (3)
Affiliations (3)
- Section of Medical Oncology, Department of Clinical Sciences, Cornell University, Ithaca, NY 14853, USA. Electronic address: [email protected].
- Section of Diagnostic Imaging, Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, Ontario, N1G 2W1, Canada.
- Section of Diagnostic Imaging, Department of Clinical Sciences, Cornell University, Ithaca, NY 14853, USA.
Abstract
Artificial intelligence (AI) serves as a decision support tool, not a replacement for clinical judgment, when used to interpret radiological images. Veterinarians retain full professional accountability for all diagnoses and treatment decisions, regardless of AI involvement. Transparency is essential: if you cannot explain to clients in understandable terms how an AI system works and its limitations, it should not be used in practice. Successful implementation requires following established best practices, including comprehensive team training, maintaining traditional diagnostic skills, and establishing quality assurance protocols.
Topics
Journal ArticleReview