Affiliation:
1. Small Animal Veterinary Surveillance Network Institute of Infection Veterinary and Ecological Sciences University of Liverpool Liverpool UK
2. Department of Computer Science Durham University Durham UK
3. Institute for Animal Health and Food Safety University of Las Palmas de Gran Canaria Las Palmas, Gran Canaria Spain
Abstract
AbstractBackgroundVeterinary clinical narratives remain a largely untapped resource for addressing complex diseases. Here we compare the ability of a large language model (ChatGPT) and a previously developed regular expression (RegexT) to identify overweight body condition scores (BCS) in veterinary narratives pertaining to companion animals.MethodsBCS values were extracted from 4415 anonymised clinical narratives using either RegexT or by appending the narrative to a prompt sent to ChatGPT, prompting the model to return the BCS information. Data were manually reviewed for comparison.ResultsThe precision of RegexT was higher (100%, 95% confidence interval [CI] 94.81%–100%) than that of ChatGPT (89.3%, 95% CI 82.75%–93.64%). However, the recall of ChatGPT (100%, 95% CI 96.18%–100%) was considerably higher than that of RegexT (72.6%, 95% CI 63.92%–79.94%).LimitationsPrior anonymisation and subtle prompt engineering are needed to improve ChatGPT output.ConclusionsLarge language models create diverse opportunities and, while complex, present an intuitive interface to information. However, they require careful implementation to avoid unpredictable errors.
Funder
Dogs Trust
Petplan Charitable Trust
British Small Animal Veterinary Association
Biotechnology and Biological Sciences Research Council
Subject
General Veterinary,General Medicine
Reference19 articles.
1. An open-label randomised clinical trial to compare the efficacy of dietary caloric restriction and physical activity for weight loss in overweight pet dogs
2. Obesity and Associated Comorbidities in People and Companion Animals: A One Health Perspective
3. Small animal disease surveillance
4. BrownTB MannB RyderN SubbiahM KaplanJ DhariwalP et al.Language models are few‐shot learners [Internet]. arXiv.org. 28 May 2020. Available from:https://arxiv.org/abs/2005.14165
5. VaswaniA ShazeerN ParmarN UszkoreitJ JonesL GomezAN et al.Attention is all you need [Internet]. arXiv.org. 2017. Available from:https://arxiv.org/abs/1706.03762
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