Vetology AI Releases Classifier Performance Metrics
Vetology AI Becomes First and Only Veterinary Imaging AI Company to Publicly Release Comprehensive Classifier Performance Metrics
Industry-Leading Transparency Directly Addresses ACVR + ECVDI Concerns, Invites Independent Studies
]JANUARY 12, 2026 — SAN DIEGO, CA — Vetology Innovations today announced the public release of complete performance metrics for all 89+ classifiers across its diagnostic platform, making it the first and only AI company in the veterinary imaging space to provide this level of transparency.
The move is an acknowledgement of the recommendations in the American College of Veterinary Radiology (ACVR) and European College of Veterinary Diagnostic Imaging (ECVDI) position statement that identified “a key challenge” in veterinary AI: “the lack of transparency and validation for AI tools currently available for veterinary diagnostic imaging.”
The joint ACVR – ECVDI statement concluded: “There is currently no commercially available product for diagnostic imaging that meets these standards” [for transparency, validation, and safety].
“We’re changing that,” said Eric Goldman, President of Vetology. “Complete transparency isn’t a competitive advantage we’re protecting, it’s a professional obligation we’re fulfilling.”
What's Now Public
Available on Vetology’s website, the data includes condition-level sensitivity, specificity, and sample sizes across 300,000 test cases covering Vetology’s canine thorax, canine abdomen, feline thorax, feline abdomen, and spine/musculoskeletal condition classifiers.
The data includes both high performers, like the heart failure classifier with 89.5% sensitivity across 10,951 cases, and more challenging applications where AI-generated screening results serve as a decision support tool within a veterinarian-led diagnostic process, requiring professional expertise and domain knowledge to interpret and validate findings.
Why This Matters
For Researchers: Vetology welcomes collaboration with the research community as part of a shared commitment to evidence-based AI in veterinary medicine. We have partnered with institutions such as AMC New York and Tufts University (among others) on peer-reviewed studies.
Building on this foundation, Vetology invites researchers to engage with us on independent validation efforts, access additional performance data, or propose collaborative studies that advance transparency, rigor, and clinically meaningful evaluation.
For Board-Certified Radiologists: Vetology is inviting radiologists to work alongside us in shaping the future of veterinary AI imaging. As these tools become more integrated into clinical workflows, radiologist expertise is essential to helping define the guardrails, best practices, and professional standards that ensure AI supports, rather than distorts, patient care.
Through collaboration around transparent performance data, radiologists can help clarify where AI aligns with real-world clinical needs, where limitations remain, and what benchmarks the profession should expect from all vendors. This partnership is about collectively defining what “good enough” means in practice, strengthening industry-wide transparency, and establishing validation approaches that protect veterinarians and the animals they serve.
For General Practitioners: Vetology views general practitioners as essential partners in the responsible use of AI at the point of care. Transparent, classifier-specific performance data supports informed clinical judgment, by helping veterinarians understand where AI can meaningfully assist, where additional scrutiny is warranted, and how uncertainty should be factored into decision-making.
This shared responsibility encourages appropriate confidence without over-reliance. It reinforces professional judgment while supporting better, more consistent care for patients, and clearer communication with pet owners. Trust your training: AI can inform the veterinarian, but it cannot replace medical insight and domain knowledge.
For Regulatory Bodies: Vetology supports collaboration with regulators in developing thoughtful, evidence-based approaches to AI oversight. Publicly available performance data provides the empirical foundation needed to move beyond one-size-fits-all regulation and toward standards that reflect real differences across conditions, modalities, and clinical use cases. By working together, regulators, clinicians, and developers can help ensure imaging AI governance evolves in a way that protects patients, supports veterinary professionals, and aligns with the nuanced oversight long advocated by leaders such as the ACVR and ECVDI.
Beyond Academic Interest: Clinical Integration That Works
“We’re releasing our performance data so veterinarians can make confident decisions in everyday practice, and so the industry can move forward in establishing clear best practices and gold standards for AI in veterinary imaging,” said Cory Clemmons, Chief Technical Officer. “Transparency is how we build trust today, and a better future for patient care.”
Practical applications include:
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- Risk-stratified triage: High-sensitivity classifiers enable confident rule-outs in screening scenarios, while moderate-sensitivity classifiers signal when additional imaging or specialist consultation adds value.
- Workflow optimization: High-confidence AI results help identify straightforward cases that may not require additional specialist review, while borderline or complex findings signal when radiologist consultation adds meaningful diagnostic value, enabling veterinary teams to allocate incremental diagnostic expenditures where they matter most for patient care.
Addressing Good Machine Learning Practice
The joint ACVR – ECVDI position statement emphasizes development “in accordance with good machine learning practices,” with particular focus on transparency, error reporting, and clinical expert involvement.
Vetology’s public metrics directly support these principles by enabling third-party evaluation, benchmarking against radiologist agreement rates, and providing visibility into both false positive and false negative characteristics through publicly reported sensitivity and specificity.
A Call to the Industry
“Every imaging AI company in this space will eventually publish performance data, either voluntarily or when regulators require it,” Goldman said. “We’re choosing to lead because transparency accelerates trust, and trust accelerates adoption of tools that genuinely help patients and practitioners.”
Vetology hopes this action encourages industry-wide adoption of open validation practices and provides a template for the kind of disclosure the ACVR and ECVDI explicitly urged.
What's Next
Vetology will update performance metrics as classifiers are retested, and publish the same comprehensive data for every new classifier launched, with new releases planned monthly. The company welcomes collaboration with academic institutions, regulatory bodies, and practicing veterinarians to refine validation methodologies and establish industry-wide standards.
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ABOUT VETOLOGY
Vetology is a veterinary imaging support company that provides AI-generated radiology reports and traditional teleradiology services by board-certified veterinary radiologists. Built by radiologists, Vetology focuses on improving patient outcomes through accuracy, speed, and reliability in diagnostic imaging. Our platform is designed to integrate seamlessly into existing hospital workflows, helping clinicians make informed decisions quickly. Learn more at vetology.net.
