AI: A Beacon of Hope in Veterinary Medicine

Dr. Abrar Ul Haq Wani      

Artificial intelligence (AI) is profoundly changing the world, with promising advancements in healthcare, and it is now on a trajectory to revolutionise the field of veterinary care. The power of AI to process massive quantities of data, recognise patterns, and make accurate predictions is opening up new possibilities for diagnosing, treating, and controlling the health of human and animal patients. In this article, we will look at how AI is changing veterinary medicine and improving the lives of both animals and their owners.

Although AI is still in its early stages in the animal health sector, scientists and entrepreneurs have successfully integrated machine learning and AI into animal health programmes in recent years. When AI initially enters an industry, it is not always welcomed with open arms because people are scared that AI will replace humans and lead to the abolition of jobs. This is not the situation in the veterinary sector; when it comes to the diagnosis and treatment of animals, nothing surpasses the expertise of a competent veterinarian. AI is a useful technology that makes a veterinarian’s job easier, faster, and with more precision, allowing them to focus on more complex jobs and the wellbeing of their patients. Despite the ethical issues, the prospects of using AI to improve our quality of life in our daily or professional activities appear unbounded. This opportunity is most apparent in medical practice. Publications on AI in medicine have mushroomed immensely during the previous two decades. There have been major breakthroughs in AI and diagnostic imaging in particular, with tools built to help in diagnosis and support radiologists in both research and commercial contexts. In veterinary medicine, a comparable transition is taking place. We are on the verge of a huge and unanticipated shift in accessible technology that has the potential to transform how veterinary care is practiced. To successfully use and deploy AI, the common veterinary practitioner does not need to have a working knowledge of computer programming. However, adopting a technology can be analogous to putting a new diagnostic test into practice. Similarly, while most veterinarians would initially be unfamiliar with the degrees of the computer algorithm built for illness diagnosis or detection, a basic level of expertise is required to grasp the power and pitfalls of AI.

Artificial intelligence in animal health care        

All veterinarians are required to understand both the potential and limits of AI. When discussing the possible applications of AI in veterinary care, AI has brought significant innovations to the veterinary sector in recent years by making veterinary diagnostics easier, medical treatment more accessible, and data harvesting for the pet market easier. Today, AI-based solutions like pet trackers and pet cameras are now in use to monitor almost every aspect of your pet’s day-to-day activities, such as movement, feeding and drinking habits, sleep patterns, and so on. This enormous volume of data provides a plethora of opportunities for machine learning. The camera provides you with an alert to check for an injury or a foreign item causing discomfort using video analytics software that is configured to detect odd behaviour. Similarly, a pet tracker discovers that your pet cat has been sleeping for many hours longer than usual each day. The tracker’s algorithm alerts you when anything is wrong with your pet cat and suggests that you contact your veterinarian. To deliver vet care, veterinary ‘Tele-health’ is in the practice that utilizes chatbots. A chatbot is software that replicates written or spoken human conversation and vet hospitals can install chatbots on their websites to act as the initial point of contact for consumers. Advanced bots might answer pet health queries and analyse symptoms in addition to aiding with communication. A pet version of the “Ada Health app” might employ a conversational interface to diagnose illnesses and give medical advice. If necessary, the app provides a remote consultation with a professional doctor. Dog walking firms such as Rover and Wag might benefit from a natural language processing (NLP) system that sends a weekly overview of their pets’ activities to their clients. Dog owners might receive a personalised email story outlining their dog’s walk routes, duration, interactions with other dogs, and food and bathroom breaks. AI-based smart feeders are also in use that could be able to identify when pet food is getting low and recommend reordering while highlighting current coupons or special discounts. Smart feeders might also track a pet’s feeding habits and flag any anomalies. Animals constantly require X-rays, and there is a shortage of veterinary imaging specialists, with even affluent private veterinary practices unable to locate and retain veterinary radiologists. AI can fill the vacuum created by these shortfalls. The good news is that AI tools for interpreting x-ray pictures are now accessible. They include cloud-based software that employs AI to scan and interpret X-rays rapidly and cheaply; your vet accesses it by registering on a website and submitting photos. The results are available nearly immediately, allowing your veterinarian to proceed with the diagnostic and treatment process. Because a picture is worth a thousand words, AI is well suited to radiology. X-rays include a wealth of data, and AI can swiftly compare past and current pictures, prioritise data, and analyse images. Veterinary radiologists are still required to evaluate complicated pictures, but AI can speed the analysis process by filtering away routine and boring x-rays, allowing veterinarians to focus on the images that require the greatest attention and the knowledge of a qualified clinician

When it comes to life-threatening disorders, it is vital to detect them early. This may appear to be impossible, but with the correct data, vets may make accurate predictions about which animals will get a disease. Chronic kidney disease (CKD) in cats is an excellent example; it is not reversible, and the patient has already incurred kidney damage by the time it manifests. It also tends to afflict older cats, so by the time a vet diagnoses CKD, the cat’s quality of life has already been significantly impaired. If the onset of CKD can be foreseen, the patient can be treated before kidney impairment develops, greatly improving the cat’s health and quality of life. Recently, researchers developed an algorithm to identify CKD in cats before they become sick. They used AI to forecast if a cat would acquire CKD within the following two years, and it was able to accomplish so with higher than 95% accuracy. This model may be readily integrated into hospital practice or diagnostic laboratory software to help vets make clinical judgements about sick cats.

It’s crucial to remember that, while AI excels at crunching figures and swiftly digesting massive amounts of data, it struggles with some of the things that humans excel at. Human talents that AI cannot replicate include creativity, problem-solving without a predetermined training dataset, and, of course, bedside manners. As a result, AI is a wonderful ally for your veterinarian. By relieving the vet of the burden of diagnosis, prediction, or data analysis, AI allows you to focus on your dog or cat’s health issues, decide on treatment plans, and ensure he has the greatest quality of life possible. Another factor to consider is how clients react to AI technology. While largely outside veterinarians’ control, client acceptance of AI will be critical to its success. Transparency and client education can help veterinary practitioners encourage acceptance. AI-powered apps and solutions for farmers and veterinarians are already on the rise, but the options continue to be limited and in the early phases of development. The future of AI in animal health is uncertain, but it is an exciting future to anticipate. What do you think? Will AI take over and play a pivotal role, or is it simply a gimmick?

Bottom-line

AI is improving the quality of care provided to animal patients in a variety of ways, including early diagnosis and treatment plans, as well as telemedicine and administrative efficiency. As AI improves and becomes more integrated into veterinary care, vets, academicians, and lawmakers must work together to maximise its benefits while ensuring the ethical and responsible use of this transformative technology. Finally, the marriage of AI with veterinary care is a promising innovation that has the potential to improve animal health and well-being for many years to come.

Dr. Abrar Ul Haq Wani, Assistant Professor cum Junior Scientist, Dept. of Medicine, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab.