Artificial intelligence and machine learning are becoming part of everyday life very rapidly. From smart watches that track your sleep to apps on your smartphone that use artificial intelligence to provide information in seconds, AI is becoming more and more commonplace.
My simplified understanding of AI is that this field of computer science is developing methods and software to enable machines to perceive their environment and use learning and intelligence to take certain actions.
Will AI become part of veterinary medicine? Will veterinarians be replaced by artificial intelligence tools, or will they use them as part of their practice?
As might be expected, the future is already here in some respects.
A previous American Animal Hospital study surveyed veterinarians, and 83 per cent of respondents were familiar with AI and nearly 30 per cent of those veterinarians were already incorporating it into their practice.
A simple example of an AI tool in veterinary medicine might be a “voice to text” tool that can transcribe a conversation between a veterinarian and a client and produce a written document that can become part of the medical record.
Medical recordkeeping is an important task, but it is usually not something that veterinarians enjoy about their job. Having a tool like this frees up the veterinarian’s time to take on more rewarding tasks.
Other examples that are already being used in agriculture include many of the software programs found in dairy barns that use robotic milkers and other advanced technologies such as pedometers, feed intake or standing/lying time. These tools can predict estrus cycles or when a cow might require treatment due to illness.
A 2020 study published in the Royal Society of Open Science investigated an ear sensor in sheep that contained an accelerometer and gyroscope.
A wide variety of these kinds of products are commercially available now that can track activities such as walking, standing and lying in a variety of livestock species. The researchers in this study were able to use this data to predict lameness in sheep with an accuracy of almost 85 per cent.
In another study, published in November 2023, researchers used an AI tool to predict body condition score in dairy cows, beef cattle and pigs by using quantitative analysis of three-dimensional shapes.
Imagine having a camera in the pasture that automatically records photos of cattle and provides an accurate estimate of their body condition on a regular basis without the producer needing to evaluate them at all.
I recently read a research paper in the November 2024 issue of Computers and Electronics in Agriculture in which researchers developed an AI tool that used retinal images in cattle to accurately diagnose cardiovascular disease.
Is cardiovascular disease the most important disease issue in beef cattle? Probably not — we see it occasionally in feedlot cattle and sometimes because of hardware disease or severe lung damage.
However, this is probably just the tip of the iceberg. New AI tools will be developed to help producers and veterinarians with the day-to-day tasks of finding and selecting sick animals, diagnosing disease and monitoring productivity.
Artificial intelligence tools are already here, and there is little doubt that the progress in this area will continue to accelerate. These tools will help to optimize the diagnostic process and enhance animal welfare.
We are probably still a long way from the day where we will be replacing animal health attendants and veterinarians with AI tools, but there will certainly be many new opportunities to explore in this exciting field.
My simplified understanding of AI is that this field of computer science is developing methods and software to enable machines to perceive their environment and use learning and intelligence to take certain actions.
Will AI become part of veterinary medicine? Will veterinarians be replaced by artificial intelligence tools, or will they use them as part of their practice?
As might be expected, the future is already here in some respects.
A previous American Animal Hospital study surveyed veterinarians, and 83 per cent of respondents were familiar with AI and nearly 30 per cent of those veterinarians were already incorporating it into their practice.
A simple example of an AI tool in veterinary medicine might be a “voice to text” tool that can transcribe a conversation between a veterinarian and a client and produce a written document that can become part of the medical record.
Medical recordkeeping is an important task, but it is usually not something that veterinarians enjoy about their job. Having a tool like this frees up the veterinarian’s time to take on more rewarding tasks.
Other examples that are already being used in agriculture include many of the software programs found in dairy barns that use robotic milkers and other advanced technologies such as pedometers, feed intake or standing/lying time. These tools can predict estrus cycles or when a cow might require treatment due to illness.
A 2020 study published in the Royal Society of Open Science investigated an ear sensor in sheep that contained an accelerometer and gyroscope.
A wide variety of these kinds of products are commercially available now that can track activities such as walking, standing and lying in a variety of livestock species. The researchers in this study were able to use this data to predict lameness in sheep with an accuracy of almost 85 per cent.
In another study, published in November 2023, researchers used an AI tool to predict body condition score in dairy cows, beef cattle and pigs by using quantitative analysis of three-dimensional shapes.
Imagine having a camera in the pasture that automatically records photos of cattle and provides an accurate estimate of their body condition on a regular basis without the producer needing to evaluate them at all.
I recently read a research paper in the November 2024 issue of Computers and Electronics in Agriculture in which researchers developed an AI tool that used retinal images in cattle to accurately diagnose cardiovascular disease.
Is cardiovascular disease the most important disease issue in beef cattle? Probably not — we see it occasionally in feedlot cattle and sometimes because of hardware disease or severe lung damage.
However, this is probably just the tip of the iceberg. New AI tools will be developed to help producers and veterinarians with the day-to-day tasks of finding and selecting sick animals, diagnosing disease and monitoring productivity.
Artificial intelligence tools are already here, and there is little doubt that the progress in this area will continue to accelerate. These tools will help to optimize the diagnostic process and enhance animal welfare.
We are probably still a long way from the day where we will be replacing animal health attendants and veterinarians with AI tools, but there will certainly be many new opportunities to explore in this exciting field.
Website: International Research Awards on Computer Vision
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