ReviewVeterinary clinical pathology2025
Artificial Intelligence in Veterinary Clinical Pathology-An Introduction and Review.
Review in Veterinary clinical pathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Artificial intelligence and laboratory biomarkers in veterinary medicine: an update about machine learning applications.The veterinary quarterly · 2026Review
- Generative AI in Veterinary Pathology: Feasibility of a GPT-Based Assistive Tool for Gross, Cytologic, and Histopathologic Assessment of Canine Cutaneous Neoplasms-A Pilot Study.Animals : an open access journal from MDPI · 2026Article
- The Expanding Role of Artificial Intelligence in Companion Animal Care: A Systematic Review.Animals : an open access journal from MDPI · 2026Review
- Artificial Intelligence in Veterinary Education: Preparing the Workforce for Clinical Applications in Diagnostics and Animal Health.Veterinary sciences · 2026Review
- Ethical considerations of artificial intelligence in veterinary medicine decision-making.Frontiers in veterinary science · 2026Review
- Curriculum framework for artificial intelligence literacy in veterinary education.Frontiers in veterinary science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI), particularly through machine learning and deep learning, presents opportunities for the enhancement of the workflow of the veterinary clinical pathologist. This review introduces basic concepts in AI in a nontechnical manner and explores the qualification and integration of AI in veterinary clinical pathology. The veterinary clinical pathologist must play an active role in defining the intended use, design, and qualification of these methods as well as the plan for monitoring their responsible application in practice.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.