Members of the Cunningham-Hollinger lab, Gifford lab and UW Meat Lab pose after a
beef harvest and data collection session at the UW Meat Lab in September 2025. Ph.D.
student Chase Markel, third from left, has created an artificial intelligence model
to predict the risk of congestive heart failure in cattle. (Cunningham-Hollinger lab
Photo)
Chase Markel, a University of Wyoming Ph.D. student from Wheatland, is harnessing
artificial intelligence (AI) to transform how animal scientists study risk factors
for congestive heart failure in cattle.
His AI model, the first of its kind, has been trained to predict the risk of congestive
heart failure based on images of a cow’s heart.
Markel, who grew up in the cattle industry, hopes that this new tool can ultimately
help alleviate financial losses associated with the condition.
Markel completed both his undergraduate and master’s degrees in the UW Department
of Animal Science. He is currently pursuing a doctorate in the same department under
the guidance of faculty advisers Hannah Cunningham-Hollinger and Cody Gifford.
As a master’s student, Markel studied pulmonary hypertension, also known as high-altitude
disease or brisket disease, in cattle. He didn’t anticipate that this animal science
research would eventually lead to a fellowship in the UW School of Computing and the
development of a “computer vision” model with the potential to revolutionize his field.
“I’m not a computer scientist. I’m not an AI guy,” Markel says. “I’m someone who is
studying heart failure (in cattle) and just happened to have the right conversation
and made the connection to build something that I think can be useful. It all started
with just trying to better understand pulmonary hypertension and heart failure.”
His master’s research indicated that subclinical cases of pulmonary hypertension,
in which an animal is affected by high-altitude disease but survives, may have larger
economic impacts than direct profit losses incurred when an animal dies before harvest.
Pulmonary hypertension has been linked to congestive heart failure, the focus of Markel’s
doctoral research. The size and shape of a cow’s right ventricle are key risk indicators
for both conditions. As pressure builds in the right ventricle, the heart becomes
thick and misshapen, increasing the severity of pulmonary hypertension and risk of
congestive heart failure.
Markel knew that detecting these abnormalities, especially in subclinical cases of
congestive heart failure, could potentially provide valuable data for plants and producers.
“Anything we can do to improve traceability and individual animal identification back
as far as we can go in the production cycle to try to prevent these things is a net
benefit for the industry,” he comments.
As a School of Computing fellow, Markel developed an image classification model calibrated
with thousands of heart images taken in commercial processing plants in Nebraska and
Colorado. He used a 1-5 scoring system developed by Tim Holt, a close collaborator
and professor at Colorado State University, to train the model to correctly categorize
images by score.
To date, Markel’s dataset includes nearly 7,000 images, each of them scored by hand
and then used to train the model. The new tool has already achieved a startling degree
of accuracy. Given an image it’s never encountered before, the AI model assigns the
correct score 92 percent of the time.
Although he continues to refine the model, Markel has provided proof of concept for
a novel approach to identifying economically relevant risk factors in individual animals.
In fact, he’s currently developing a similar model to evaluate liver images for the
presence and severity of liver abscesses, another common affliction in feedlot cattle.
“As researchers, we need to start incorporating these tools into our research and
… build that technology so producers and people out in the industry can actually utilize
those tools and help improve their bottom line,” he says.
While Markel’s current models are best suited for application in processing plants,
he hopes that future iterations will benefit Wyoming producers more directly.
“Chase Markel’s research exemplifies our college’s commitment to conducting Wyoming-relevant
research, which integrates emerging technologies, producer experiences and UW faculty
expertise to address some of Wyoming agriculture’s most vexing challenges,” says Kelly
Crane, Farm Credit Services of America Dean in the College of Agriculture, Life Sciences
and Natural Resources.
Markel submitted a provisional patent application to the U.S. Patent and Trademark
Office through UW in 2025. He hopes to obtain full patent protection in 2026.
For questions about Markel’s research, email cmarkel1@uwyo.edu.
About the UW College of Agriculture, Life Sciences and Natural Resources
The University of Wyoming College of Agriculture, Life Sciences and Natural Resources
serves students and communities through innovative scholarship, research and outreach.
Guided by the land-grant principles of discovery and experiential learning, the college
facilitates meaningful educational opportunities in the classroom, laboratory and
community. The college offers degrees in the departments of agricultural and applied
economics, animal science, botany, ecosystem science and management, family and consumer
sciences, molecular biology, plant sciences, veterinary sciences, and zoology and
physiology. The college also offers degree programs in agricultural communications,
microbiology, and ranch management and agricultural leadership. To learn more, visit
www.uwyo.edu/uwag or call (307) 766-4133.
