ArticleThe veterinary quarterly2026
AI-assisted post-mortem classification of vehicle trauma in free-roaming cats using transformer-based large language models.
Article in The veterinary quarterly, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Veterinary forensic science is a specialized discipline that investigates non-natural animal deaths and injuries. Determining the cause of death in free-roaming cats often presents challenges due to underdeveloped pattern recognition methods and the intricate interplay of events and contributing factors. The integration of natural language processing into forensic investigations may offer potential for the computerized automation of document analysis, with the goal of supporting investigational decision-making. The objective of this study was to develop an AI framework leveraging a transformer-based large language model (LLM) to classify veterinary forensic autopsy reports derived from 271 feline autopsies and to identify the causes of death. We first identified discriminative lexical patterns between vehicular trauma (VT;
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