Veterinary & One Health AI
Extending clinical AI expertise to animal health and zoonotic disease surveillance
Industry Challenge
One Health — the recognition that human, animal, and environmental health are interconnected — is driving investment in veterinary AI for diagnostics, disease surveillance, and antimicrobial resistance tracking. Veterinary AI models require annotated imaging, clinical records, and laboratory data labeled by professionals with veterinary clinical knowledge.
How SCILabel Serves This Industry
Data Collection
We source de-identified veterinary radiographs, histopathology slides, clinical records, and zoonotic disease surveillance datasets from veterinary schools, agricultural research institutes, and One Health research programmes.
Data Annotation & Labeling
Our veterinary-trained annotators — Veterinary Officers, Animal Health Technologists — label veterinary radiographs for fractures and orthopaedic conditions, annotate histopathology slides for animal tissue pathology, and structure zoonotic disease surveillance records for epidemiological AI.
Data & Model Evaluation
Evaluators benchmark veterinary diagnostic AI performance against veterinarian ground truth and assess zoonotic disease detection model sensitivity for early outbreak signal detection.
Annotation Types & Formats
- Veterinary radiograph annotation: fractures, orthopaedic, dental
- Animal histopathology annotation: tissue classification, neoplasia grading
- Zoonotic disease case annotation on surveillance records
- Antimicrobial resistance pattern classification
Specialist Workforce Tracks
Track 2 (Medical Imaging) and Track 4 (Genomics & Biomedical): Veterinary Officers, Animal Health Technologists, Biomedical Scientists.