ArticleJournal of veterinary internal medicine2026
The influence, promise, and potential perils of artificial intelligence in veterinary medicine: a call for improved awareness and literacy.
Article in Journal of veterinary internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly becoming integrated into daily lives, including tasks unique to our professional domains. With technology outpacing the general knowledge base regarding veterinary AI tools, we are at a critical inflection point in our American College of Veterinary Internal Medicine (ACVIM) and European College of Veterinary Internal Medicine - Companion Animals (ECVIM-CA) community. This manuscript presents a perspective aimed at igniting a broader and deeper discussion of, and engagement with, AI tools among members and enhancing members' AI literacy where necessary. The ACVIM AI Task Force encourages members to become actively involved in the processes that determine where, when, and how AI technology is adopted in our fields of expertise. Collectively, the principles outlined here promote thoughtful, transparent innovations while upholding standards of modern healthcare. However, it behooves us as potential users to support the need for critical oversight to evaluate and verify the safety and efficacy of AI tools in the routine patient care. To aid with an initial review of AI tools before use, a novel ACVIM AI Validation Factor checklist is introduced.
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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 OpenQuestion graph.