ArticleScientific reports2025
Comparison between AI and human expert performance in acute pain assessment in sheep.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Comparing the performance of deep learning video-based models and trained veterinarians in cattle pain assessment.Scientific reports · 2026Article
- Empathy for pain in humans and animals differs based on species, psychosocial and cultural factors.Scientific reports · 2026Article
- Feasibility and reliability of pressure algometry for mechanical nociceptive threshold quantification in lambs in a field environment.Frontiers in pain research (Lausanne, Switzerland) · 2026Article
- What Does That Head Tilt Mean? Brain Lateralization and Sex Differences in the Processing of Familiar Human Speech by Domestic Dogs.Animals : an open access journal from MDPI · 2025Article
- First steps in the development of an ovine proximal phalanx fracture and bone defect model: a study of animal welfare and bone healing.Frontiers in veterinary science · 2025Article
- Proteolytic enzyme models as tunable preclinical platforms for investigating intervertebral disc degeneration.Frontiers in cell and developmental biology · 2025Review
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Authors and funding
7 authors.
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Abstract
This study explores the question whether Artificial Intelligence (AI) can outperform human experts in animal pain recognition using sheep as a case study. It uses a dataset of N = 48 sheep undergoing surgery with video recordings taken before (no pain) and after (pain) surgery. Four veterinary experts used two types of pain scoring scales: the sheep facial expression scale (SFPES) and the Unesp-Botucatu composite behavioral scale (USAPS), which is the 'golden standard' in sheep pain assessment. The developed AI pipeline based on CLIP encoder significantly outperformed human facial scoring (AUC difference = 0.115, p < 0.001) when having access to the same visual information (front and lateral face images). It further effectively equaled human USAPS behavioral scoring (AUC difference = 0.027, p = 0.163), but the small improvement was not statistically significant. The fact that the machine can outperform human experts in recognizing pain in sheep when exposed to the same visual information has significant implications for clinical practice, which warrant further scientific discussion.
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