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Clinical

A review of applications of artificial intelligence in veterinary medicine

02 June 2023

Professional

17 mins read

02 June 2023

Volume 28 · Issue 6

ISSN (print): 2053-0889

ISSN (online): 2053-0897

Figure 1. Schematic illustration showing deep learning as a subfield of machine learning, while both are part of artificial intelligence.

Abstract

Artificial intelligence is a newer concept in veterinary medicine than human medicine, but its existing benefits illustrate the significant potential it may also have in this field. This article reviews the application of artificial intelligence to various fields of veterinary medicine. Successful integration of different artificial intelligence strategies can offer practical solutions to issues, such as time pressure, in practice. Several databases were searched to identify literature on the application of artificial intelligence in veterinary medicine. Exclusion and inclusion criteria were applied to obtain relevant papers. There was evidence for an acceleration of artificial intelligence research in recent years, particularly for diagnostics and imaging. Some of the benefits of using artificial intelligence included standardisation, increased efficiency, and a reduction in the need for expertise in particular fields. However, limitations identified in the literature included a requirement for ideal situations for artificial intelligence to achieve accuracy and other inherent, unresolved issues. Ethical considerations and a hesitancy to engage with artificial intelligence, by both the public and veterinarians, are further barriers that must be addressed for artificial intelligence to be fully integrated in daily practice. The rapid growth in artificial intelligence research substantiates its potential to improve veterinary practice.

John McCarthy first coined the term artificial intelligence (AI) in 1956 while lecturing at Dartmouth College (Bini, 2018). Although the term has now been integrated into everyday life, there is no standard accepted definition for AI (Samoili et al, 2020). One of the numerous definitions for AI is ‘a system's ability to interpret external data correctly, to learn from such data and to use that learning to achieve specific goals and tasks through flexible adaptation’ (Kaplan and Haenlein, 2019). Currently, AI is more integrated into the practice and research of human medicine than it is into veterinary medicine, but many of its applications, such as imaging, diagnostics, and health records, are equally relevant to veterinary medicine. As an example, medical coding infrastructure of health records to aid doctors and improve clinical research is already established in human medicine. Similarly, veterinary research is now examining the large scale use of electronic health records to predict diagnoses from free text clinician notes (Zhang et al, 2019). This information can then be used for several purposes including research and public health.

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machine learning

deep learning

artificial intelligence

companion animals

veterinary