Prashnna Gyawali, assistant professor in the Lane Department of Computer Science and Electrical Engineering at the WVU Benjamin M. Statler College of Engineering and Mineral Resources, said heart failure—a chronic, persistent condition in which the heart cannot pump enough blood to meet the body’s need for oxygen—is one of the most pressing national and global health issues, and one that hits rural regions of the U.S. especially hard.

Despite the outsized impact of heart failure on rural populations, AI models are currently being trained to diagnose the disease using data representing patients from urban and suburban areas like Stanford, California, Gyawali said.

“Imagine Jane Doe, a 62-year-old woman living in a rural Appalachian community,” he suggested. “She has limited access to specialty care, relies on a small local clinic, and her lifestyle, diet and health history reflect the realities of her environment: high physical labor, minimal preventive care, and increased exposure to environmental risk factors like coal dust or poor air quality. Jane begins to experience fatigue and shortness of breath—symptoms that could point to heart failure.