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  11. Veterinary Students Exhibit Low Artificial Intelligence Literacy But Agree It Will Be Deployed To Improve Veterinary Medicine.
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Veterinary students exhibit low artificial intelligence literacy but agree it will be deployed to improve veterinary medicine.

Krystle L Reagan1, Karen Boudreaux2, Stefan M Keller3

  • 1Department of Veterinary Medicine and Epidemiology, School of Veterinary Medicine, University of California-Davis, Davis, CA.

American Journal of Veterinary Research
|May 20, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

Veterinary students show limited knowledge but high interest in artificial intelligence and machine learning (AI/ML). Most anticipate using AI/ML in practice, highlighting the need for curriculum integration.

Keywords:
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Area of Science:

  • Veterinary Medicine
  • Artificial Intelligence
  • Machine Learning

Background:

  • Artificial intelligence and machine learning (AI/ML) are rapidly advancing.
  • AI/ML applications are becoming increasingly prevalent in veterinary medicine.
  • Understanding veterinary students' perceptions of AI/ML is crucial for future integration.

Purpose of the Study:

  • To assess the knowledge and perceptions of AI/ML among veterinary students.
  • To gauge student interest in AI/ML within veterinary medicine.
  • To identify gaps in current veterinary curricula regarding AI/ML.

Main Methods:

  • A cross-sectional survey was administered to veterinary students at the University of California-Davis.
  • The survey collected data on students' knowledge, attitudes, and exposure to AI/ML.
veterinary education
  • Descriptive statistics were used to analyze the survey responses.

    • Main Results:

    • 80% of surveyed students reported little to no knowledge of AI/ML.
    • 79% expressed moderate to extreme interest in learning about AI/ML applications.
    • 59% expect to use AI/ML tools in their future practice, and 77% believe AI/ML will improve veterinary medicine.

    Conclusions:

    • Veterinary students possess a strong interest in AI/ML and recognize its future importance.
    • Current veterinary curricula inadequately address AI/ML literacy.
    • Educational programs should incorporate AI/ML to prepare future veterinarians for clinical practice.