Mars Petcare Will Talk About Tech at VMX

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Press release: Mars Petcare

Pets can’t tell us what’s ailing them. But today, we have new technologies and artificial intelligence that are giving us insight into their health and behaviors that we haven’t been able to access until now.

This year at the Veterinary Meeting & Expo in Orlando, Florida, Mars Petcare will present a session on January 20 about new technologies that can drive preventive care in veterinary practices. The latest technologies and tools driving preventive care will be discussed, along with how they are strengthening the relationships between veterinarians and pet owners on proactive health and wellness.

Topics of discussion and speakers are:

• Pet Insight Project: Aletha Carson, DVM, will lead a conversation about how our pets’ behavior has hidden insights into their well-being. In the past two years, we’ve quantified and analyzed over 10 million days of behavioral information from over 90,000 dogs using Whistle FIT monitors to capture those behaviors and help determine how they relate to our pets’ overall well-being. We will share new discoveries about the early identification of health issues, such as dermatologic (skin) disorders via monitoring of a dog’s round-the-clock behavior, including sleep patterns, scratching habits and barking using the Whistle FIT smart collar.
• WISDOM PANEL: Angela Hughes, DVM Ph.D., will show how this canine DNA test is providing new insights for veterinarians into the specific health needs of dogs through the extensive ancestry and genetic health screening for more than 150 conditions. We’ll share findings from the large-scale integration of Wisdom Panel Health genetic testing into the Banfield Pet Hospital Puppy Optimum Wellness Plans, which has tested 200,000 puppies in just over a year, including 5 percent who have actionable health insights identified in their DNA.
• RenalTech: Jennifer Ogeer, DVM, will share background on the first predictive tool in veterinary medicine that uses artificial intelligence and machine learning to predict whether a cat will develop chronic kidney disease – a disease that affects 30-40 percent of cats over the age of 10 – two years before typical clinical diagnosis offering new avenues for monitoring and treatment to improve the health and well-being of our feline patients.