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An Introduction to Artificial Intelligence and Machine Learning for Veterinary Professionals.

Christopher Pinard¹

¹Department of Oncology, Toronto Animal Cancer Centre, Toronto, Ontario, Canada; ANI.ML Research, ANI.ML Health Inc., Toronto, Ontario, Canada; Department of Small Animal Clinical Sciences, University of Saskatoon, Saskatoon, Saskatchewan, Canada; Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI), University of Guelph, Guelph, Ontario, Canada.

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Summary

This summary is machine-generated.

Artificial intelligence (AI) and machine learning (ML) offer new tools for veterinary medicine. This guide explains AI/ML concepts, algorithms, and implementation for veterinary professionals.

Keywords:

Artificial intelligence Clinical decision support Computer vision Deep learning Machine learning Natural language processing Neural networks Veterinary medicine

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Area of Science:

Veterinary Medicine
Artificial Intelligence
Machine Learning

Background:

Artificial intelligence (AI) and machine learning (ML) are gaining traction in veterinary practice.
Veterinary professionals require a foundational understanding of these technologies.

Purpose of the Study:

To provide veterinary professionals with a clear understanding of AI and ML concepts.
To discuss key terminology, evaluation metrics, and clinical implementation considerations.
To empower professionals to evaluate and adopt AI-based veterinary tools.

Main Methods:

Explanation of AI, ML, and deep learning distinctions.
Overview of supervised, unsupervised, and reinforcement learning paradigms.
Discussion of common algorithms (decision trees, random forests, SVMs, neural networks).

Main Results:

Veterinary professionals will gain knowledge of AI/ML fundamentals.
Understanding of model evaluation and practical clinical application is provided.
Preparedness to engage with AI development in veterinary medicine.

Conclusions:

Foundational AI/ML knowledge is crucial for veterinary professionals.
This understanding facilitates the evaluation and adoption of AI tools.
Professionals can actively contribute to AI advancements in veterinary practice.