Artificial intelligence in veterinary diagnostics

Artificial intelligence has become commonplace, helping users select the next song on a playlist or the next word in a message. As it continues to develop, its use will also become routine in veterinary practice. As with any new technology developed within the profession, it is important to understand its application and how it works.

Many areas of veterinary medicine will benefit from the development of artificial intelligence, with research already showing how it can be applied for disease surveillance (Bollig et al, 2020) and predicting disease development within a population (Biourge et al, 2020). One of the areas where its use has already been demonstrated is in the diagnosis of disease. Technology that helps to make faster diagnoses with greater confidence will expedite how veterinary medicine is practised, allowing more time for other vital tasks.

Artificial intelligence is the development of technology that allows computer systems to perform tasks that would previously have required human intelligence. There are several different types of artificial intelligence. The subset that has been most investigated in veterinary medicine is machine learning, which is where sample data is used to train a system to recognise patterns and learn without explicit instructions (Cui et al, 2020), for example, a social media platform correctly grouping photographs of the same person. Deep learning is a subset of machine learning, and these models are made up of neuronal networks. Neuronal networks are based on neurons in the human brain and act to receive and process information before giving an output (Cui et al, 2020).