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New horizons: Artificial intelligence in veterinary medicine

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"AI will likely diffuse into clinical practice in small but tangible ways that could release the burden of what might be considered mundane tasks...Those time-savings can be re-invested into more patients accessing care or other clinical tasks." -Dr. Parminder Basran

The December 2022 issue of the journal Veterinary Radiology & Ultrasound was singularly focused on a hot topic in medicine — artificial intelligence (AI). The journal tapped The Cornell University College of Veterinary Medicine (CVM)’s Dr. Parminder Basran, radiation oncology physicist and associate research professor and Dr. Ian Porter, veterinary radiologist and assistant clinical professor, both in the in the Department of Clinical Sciences, along with colleagues at the University of Tennessee and Colorado State University, to provide a series of review articles on the topic.

The open access articles, entitled “Artificial intelligence 101 for veterinary diagnostic imaging,” “Radiomics in veterinary medicine: Overview, methods, and applications,” and “The role of artificial intelligence in veterinary radiation oncology,” are meant to give a broad overview on the topic. “These articles provide a great starting point for anyone who wants to learn about AI and veterinary medicine,” says Basran. “While much of the focus is on diagnostic imaging, many of the articles cover topics broad enough to provide a general understanding of the AI-related subjects. They’re an accessible and readable set of articles that the community will (hopefully) enjoy.”

We had a chance to ask Basran more about AI in veterinary medicine today, and where it might take us in the future.

Q: How is AI being harnessed to help improve veterinary medicine?

Most applications of AI in veterinary medicine are academic in nature, with a few exceptions of commercial products. Some products currently available in veterinary medicine include automated analysis of x-ray radiographs. As the pace of this technology is increasing rapidly, one can expect to see some forms of AI adopted in veterinary applications.

Q: Can you provide a specific example of how AI has dramatically changed how veterinary medicine is being done?

We have not seen AI dramatically change the practice of veterinary medicine yet, but there is a lot of potential. I firmly believe Cornell is well-positioned to lead the way in this regard.

Q: What is on the horizon for this field of work? What new breakthroughs or changes might we see in AI-assisted veterinary medicine?

AI will likely diffuse into clinical practice in small but tangible ways that could release the burden of what might be considered mundane tasks. A key example we discussed in our review paper focuses on the practice of radiation oncology. When delivering high-precision radiation treatments, it is necessary to obtain a 3D image dataset of the patient, typically with x-ray computed tomography (CT or CAT scans). The radiation oncologist then draws the tumor/target and the surrounding normal tissues on each slice of the CT scan (segmentation). This is an important but very time-consuming step, typically taking anywhere from one to four hours per patient. AI-based auto-segmentation has been explored in human medicine and can save time (30% or more) while also providing a consistent approach to segmentation (reduce inter- and intra-observer variations). Those time-savings can be re-invested into more patients accessing care or other clinical tasks.

Q: What might you say to a veterinarian who might be interested in leveraging AI in their research or clinical work, but might be intimidated or not know how to begin?

First, don’t be intimidated, especially if you have been in the profession for a long time.

Second, flip through these review articles to get a sense of what AI can bring to your practice. What we are learning in human medicine is that AI-based medicine is not a panacea but rather a tool that can alleviate burdensome tasks or reveal options you may not have considered.

Third, I think it is critical to think about the ethical and legal implications of introducing AI in the health. We need to think about how AI affects our decision making, resolve and understand biases, especially since veterinarians play a critical role in the quality of life of animals and those who care for them.

Finally, when it comes to clinical implementation, we should think of the integration of AI in clinical practice in the same way we introduce any new major technology into clinical practice. When we, for example, receive major equipment or software which can change the way we practice, we need to assemble stakeholders from all relevant disciplines, and devise a plan.

These plans should include:

a) determining priorities and selecting AI technologies carefully;

 b) commissioning AI technologies where we can understand what data was used to develop models, establish benchmarks for performance with validated data;

c) introduce these technologies with solid training and education so that veterinarians understand the benefits and limitations of the technology;

d) continuously evaluate performance of the AI technologies subjected to our clinical data;

e) figure out how we might be able to improve upon these technologies by ‘retraining’ or ‘adapting’ AI algorithms based on the current standards of care and patient demographic profiles in our practices. Such a team should consist of data scientists, clinicians, administrators, and other professionals who touch AI technologies.

Q: Could AI make radiologists obsolete?

I love the quote by Dr. Curt Langlotz, Professor of Radiology and Biomedical Informatics who said: “Radiologists will not be replaced by AI. Radiologists who use and understand AI will replace radiologists who don't.”

Q: How is AI being used in human medicine today, and how far does veterinary medicine have to go to catch up?

We are seeing a LOT of new applications, ranging from Chatbots, AI-based radiology reporting, COVID-19 tracking… there are just too many to list. Veterinary medicine has a fair bit of catching up to do. A critical challenge veterinary medicine faces is that the species we treat can have so many anatomical and physiological differences (e.g., running a CT auto segmentation algorithm trained on images of Great Danes would probably perform poorly on a CT scan of Chihuahua!)

Q: What must veterinary medical institutions do to begin matching human medicine in this way?

We need tackle this challenge with training and education. Veterinarians trained in our schools today WILL be using AI technologies. We need to train future veterinarians to think about questions they should be asking when AI technologies present themselves in the clinic. We need educational courses and training for existing veterinarians so they don’t get left in the dark. This is a tough task since more we learn, the more we know, but we also learn what we DON’T know. We touch on these things in the articles.

Q: What excites you most about this field?

Cornell University is a global leader in computing science and AI development and with Weill Cornell Medicine, there are tremendous opportunities to leverage all this expertise and find novel ways in which AI can help our veterinarians work more efficiently and smarter. The Cornell University Hospital for Animals hospital has made some tremendous strides in building an exceptional data-infrastructure. This hard work is unseen but critical and establishes CVM as a gold mine of accessible and useable data. Bringing the data, scientists, and clinicians together is always a challenge, but CVM is in a great spot to lead the way globally. Personally, I love connecting with faculty and researchers from broad and diverse disciplines. CVM is an exceptional environment where veterinary AI can flourish.

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Trending Topics

Trending Issues in Veterinary Medicine for 2023 and Beyond

On the surface, 2022 appears a successful year for veterinary practices , with many reporting strong revenues as pandemic restrictions and mandates receded. However, dig a little deeper, and you'll see a range of trending issues veterinary practices will need to address through 2023 and beyond if they want the success to continue.

While none of us has a crystal ball, we can make an educated guess at what comes next. Read on for the issues in veterinary medicine that we see in our practice now and expect to see in the future.

  Elevate patient care without overwhelming staff. Learn how.

Veterinary Trends Today

Some issues are perennial, from finding and retaining the right team members to keeping clients happy. Some of those issues have been, and will likely continue to be, made worse by factors well outside of our industry.

• New team members: The historically low unemployment rate continues to affect our ability to find and hire qualified team members. For veterinarians, the problem is even worse: Mars Veterinary Health estimates that by 2030, a shortage of nearly 15,000 doctors in veterinary medicine will exist. It's time to get inventive and engage with the community to build relationships before you need people. You might also involve your team more, paying bonuses for new hires they bring in.
• Veterinary burnout: Adding to the challenge is the loss of people from the industry through burnout and compassion fatigue. As owners, we need to support and retain our teams , recognize the consequences of expecting them to do more with less, and protect them as best we can in conflicts with pet owners. Even with everything else we have going on, keeping a regular pulse on your team's morale should be a top priority to avoid losing people.
• Product shortages: It's not just new team members that have been hard to find this year. Several major products have also gone on long-term backorder. Supply chain issues are hitting even the biggest vendors—and that affects our practice's protocols and revenues. It's certainly frustrating, but you can minimize the damage by streamlining the process to approve new products and protocols with your medical team. Nurturing relationships with vendors also can help get sought-after products on the shelves faster.
• Online pet pharmacies: Online commerce isn't going away, and the allure extends to pharmacies, which can offer lower costs and more convenience online. With Walmart entering the market and Amazon increasing the range of products it provides, it's going to become increasingly difficult to justify preventing our clients from buying online. Rather than creating extra conflict for your team to deal with, it might be wise to partner with one or more pharmacies to capture at least some revenue there.
• Inflation and recession: It seems impossible to talk about short-term trends without considering the elephant in the room: the current inflation rate and other macroeconomic factors that are driving up costs. This makes it essential to keep a close eye on your practice's finances, identify where you save money, and make sure you are passing costs onto clients so that your profit margins don't plummet.

Veterinary Trends for the Future

While our current issues in veterinary medicine may seem daunting, there are reasons to be optimistic. The following trends will hopefully lead to exciting changes that make the industry more rewarding right now and over the long term:

• Medical advances: The last few years have seen incredible advances from the pharmaceutical industry that are changing the way we practice medicine. I'm particularly excited about monoclonal antibody therapies; the ones we have witnessed so far seem game-changing for our patients. Working with your medical team to assess new products and ideas—including new veterinary software —as they come to market is a critical way to ensure you're not only offering the best service to your clients and patients but also encouraging the development of new products by providing an end market for them.
• Transition to services: As with human medicine, we are seeing a transition toward a service-based model within our facilities. We expect to see a continued decline in pharmacy sales as we focus more on delivering in-practice treatments and building long-term client and patient relationships. Think of this as an extension of the transition from annual vaccines to yearly comprehensive wellness checkups.
• In-house labs: Using in-house machines in conjunction with our reference lab can help us work more effectively with clients. Not only can we present results to the client while they're still in the practice, but it increases the uptake of treatment recommendations. With continuing advances in artificial intelligence technology, I expect more and better in-practice and cloud-supported diagnostic tools to become available.
• Pet insurance: With all of the advances we're expecting, costs will continue to challenge our clients. Pet insurance may fill that gap. As managers, we're going to have to figure out how we interface with an industry expected to grow by the billion . As such, it's important to work with our clients to understand their coverage and payment options.

Becoming Leaders, Not Followers

While we may not understand—or even like—the trends we see in veterinary medicine today and the ones we expect tomorrow, it's nevertheless essential as industry professionals for us to watch and learn from developments in the space and incorporate the best of them into our practice management. In that way, we can cultivate a practice that leads, not follows.

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Des Whittall is an owner and manager of two veterinary clinics and pet resorts in Texas. A software engineer by training, he worked with an investment bank for 13 years in roles ranging from technical support to business divestment, managing large international teams and complex vendor relationships. With his partner, he has grown the clinics and resorts and is focused on developing businesses that can provide high-quality medicine and development opportunities for their teams.

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