Artificial Intelligence in Veterinary Medicine
by Jenny Alonge
Artificial intelligence (AI) is an important technological advancement that is emerging in many industries, including veterinary medicine. AI will never replace a veterinarian’s knowledge or skills but may improve the veterinary team’s efficiency and productivity, and help diagnose certain conditions. Let’s take a look at some AI tools currently available or up and coming in the veterinary field.
DeepTag
Unlike the U.S. human healthcare system, veterinary medicine has no standardized medical coding infrastructure, which hinders clinical research and public health monitoring. DeepTag was developed by James Zou, PhD, as an AI solution to this problem.
DeepTag is an algorithm that reads typed veterinary medical notes that are transferred into codes representing certain ailments, disease signs, or conditions. To train the algorithm, Dr. Zou collaborated with veterinary experts who annotated more than 100,000 clinical notes, assigning specific disease codes to each case. Researchers further validated the algorithm’s accuracy by testing pet clinical data from private veterinary offices. Once the platform launches, DeepTag should help veterinarians track disease prevalence in pets and may be used to track pet clinical trials.
Radiomics
Radiomics is quantitative image analysis based on radiographic image data. AI techniques are being actively developed and used in veterinary radiology to improve diagnostic image quality, workflow efficiency, and interpretation of patient images. Veterinary radiation oncology applications for treating cancer patients are also on the horizon. Platforms include:
- SignalPET® — SignalPET’s patented process uses machine learning to develop normals based on millions of radiograph data points. SignalPET products include:
- SignalRAY®, which provides radiology test panels for the most common clinical findings powered by AI
- SignalRAY+, which allows the user to add history to refine clinical answers
- SignalSMILE®, which provides dental radiology test panels for the most common dental pathologies powered by AI
- Vetology — Vetology, which was developed by radiologists, provides virtual radiology reports in minutes and also offers a review of the AI radiology report by a board-certified veterinary radiologist.
- Radimal — Radimal connects directly to the practice’s X-ray machine to automatically provide AI-powered insights on all X-rays and allows users to request a DACVR board-certified specialist consultation.
- PicoxIA — PicoxIA provides automatically generated reports for processed anatomic regions, including:
- Abdomen — Provides thirteen detected patterns and three differential diagnosis suggestions and automatically computes kidney size
- Thorax — Sixteen detected patterns and four differential diagnosis suggestions, and automatically plots the vertebral heart scale (VHS)
- Hip dysplasia — Provides five detected patterns and automatically plots Norberg-Olsson angles
RenalTech®
Antech’s RenalTech® was developed using AI and machine learning and leveraged historical patient data that included 700,000 veterinary visits and 150,000 cats over more than 20 years. The technology can predict feline chronic kidney disease (CKD) as early as two years before diagnostic changes with 95% accuracy. RenalTech® uses blood urea nitrogen (BUN), creatinine, urine specific gravity, urine protein, urine pH, white blood cell count, and age to produce a value that indicates a cat’s likelihood of developing CKD. This knowledge helps the veterinarian develop a personalized patient care plan to help mitigate signs and slow disease progression.
Canine hypoadrenocorticism diagnosis
Canine hypoadrenocorticism (CHA) is notoriously difficult to diagnose, because dogs exhibit a wide array of clinical presentations and the condition often mimics other diseases, such as kidney disease, gastrointestinal (GI) disease, and hepatic insufficiency. Veterinary researchers at the University of California, Davis, School of Veterinary Medicine developed an algorithm with greater than 99% accuracy that uses AI to detect CHA. The research team used complete blood count (CBC) and biochemistry profile results from more than 1,000 dogs to train the AI program, which can alert veterinarians that CHA is suspected, so they can perform other diagnostic tests to confirm the diagnosis.
Stethee Vet
Stethee Vet is an AI-enabled stethoscope that allows users to listen and instantly capture heart and lung sounds using sophisticated amplification and filtering technology. Stethee’s AI engine, “Aida,” analyzes heart and lung sounds to build a unique biometric signature and can signal the presence of conditions such as a heart arrhythmia or murmur. In addition, the technology allows support staff to triage and collect samples for the veterinarian’s clinical assessment.
PetsApp
PetsApp is an AI platform aimed at improving a veterinary practice’s customer service by complementing human expertise. Tools include:
- Appointment requests or bookings — Veterinarians can approve or decline requests in the app’s dashboard, and bookings sync with the PMS.
- Campaigns — Users can contact all clients or particular audiences with newsletters, promos, or seasonal information.
- Unlimited two-way SMS and app messages — Clients can easily contact the veterinarian through SMS or an app message.
- Digital payments — Veterinarians can receive digital payments from their clients through the app for 2.9% + 30 cents.
- Reminders — Veterinarians can remind clients about appointments and medication compliance via push notifications, SMS, and emails.
AI is a hot topic, and these tools, used appropriately, can make a veterinarian’s life a little easier and help improve the veterinary team’s productivity and efficiency.
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