AI predicts heart failure risk in cattle

Thousands of cattle heart images are being used to train an AI model that helps identify early risk factors for congestive heart failure in commercial livestock.
Computer vision technology developed at a US university can now assess heart failure risk in cattle by analysing thousands of processing plant images with high accuracy.

Researchers at the University of Wyoming in the US have developed an AI model that predicts the risk of congestive heart failure in cattle using heart images. The technology focuses on structural changes linked to pulmonary hypertension.

Developed by PhD researcher Chase Markel, the computer vision system was trained on nearly 7,000 manually scored images. The model correctly classifies heart risk levels in 92 percent of cases.

The images were collected in commercial cattle processing plants, allowing assessment at scale after slaughter. The findings support the need for improved traceability throughout the production cycle.

Industry use could enhance traceability and mitigate economic losses resulting from undetected disease. Patent protection is being pursued as further models are developed for other cattle conditions.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!