EDITORIAL article
Front. Vet. Sci.
Sec. Veterinary Imaging
Editorial: Monitoring and Reducing Errors in Veterinary Radiology
University of Veterinary Medicine Vienna, Vienna, Austria
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Abstract
Diagnostic imaging stands at the center of modern veterinary medicine. It informs therapeutic 3 decisions, guides surgical planning, and increasingly shapes outcome discussion. Yet, despite 4 remarkable technological progress, diagnostic error remains an inherent and universal feature of 5 radiologic practice. Errors may arise from perceptual or cognitive failure, methodological or 6 technological constraints, or systemic pressures. Recognizing this reality is not a sign of 7 weakness in the discipline-it is a necessary step toward strengthening it. 8The
Summary
Keywords
artificial intelligence, cat, Discrepancy, dog, error, horse, machine learning, Veterinary diagnostic imaging
Received
06 February 2026
Accepted
19 February 2026
Copyright
© 2026 Kneissl. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Sibylle Maria Kneissl
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.