ChatGPT in Veterinary Medicine: A Practical Guidance of Generative Artificial Intelligence in Clinics, Education, and Research
<|reference_start|>ChatGPT in Veterinary Medicine: A Practical Guidance of Generative Artificial Intelligence in Clinics, Education, and Research: ChatGPT, the most accessible generative artificial intelligence (AI) tool, offers considerable potential for veterinary medicine, yet a dedicated review of its specific applications is lacking. This review concisely synthesizes the latest research and practical applications of ChatGPT within the clinical, educational, and research domains of veterinary medicine. It intends to provide specific guidance and actionable examples of how generative AI can be directly utilized by veterinary professionals without a programming background. For practitioners, ChatGPT can extract patient data, generate progress notes, and potentially assist in diagnosing complex cases. Veterinary educators can create custom GPTs for student support, while students can utilize ChatGPT for exam preparation. ChatGPT can aid in academic writing tasks in research, but veterinary publishers have set specific requirements for authors to follow. Despite its transformative potential, careful use is essential to avoid pitfalls like hallucination. This review addresses ethical considerations, provides learning resources, and offers tangible examples to guide responsible implementation. Carefully selected, up-to-date links to platforms that host large language models are provided for advanced readers with programming capability. A table of key takeaways was provided to summarize this review. By highlighting potential benefits and limitations, this review equips veterinarians, educators, and researchers to harness the power of ChatGPT effectively.<|reference_end|>
@article{chu2024chatgpt,
    title={ChatGPT in Veterinary Medicine: A Practical Guidance of Generative
  Artificial Intelligence in Clinics, Education, and Research},
    author={Candice P. Chu},
    journal={arXiv preprint arXiv:2403.14654},
    year={2024},
    doi={10.3389/fvets.2024.1395934},
    archivePrefix={arXiv},
    eprint={2403.14654},
    primaryClass={cs.CY}
}