Research Highlights:
Embargoed until 4 a.m. CT/5 a.m. ET, Monday, Nov. 2, 2026
This news release contains updated information not available in the abstract.
DALLAS, Nov. 2, 2026 — Artificial intelligence (AI) helped health professionals with no ultrasound experience in capturing quality heart scans in rural communities, which were then reviewed by off-site experts, according to independent, new preliminary research to be presented at the American Heart Association’s Scientific Sessions 2026 . The meeting, Nov. 6-9, in Chicago, is a premier global exchange of the latest scientific advancements, research and evidence-based clinical practice updates in cardiovascular science.
Echocardiography, or ultrasound scans of the heart, performed with AI assistance and reviewed by experts in other locations, may be one way to bring heart imaging to people living in rural communities. Echocardiography uses ultrasound to give live, moving images of the heart’s structure and function.
According to the American Heart Association , your health care professional may order this test if you have a heart murmur, damaged heart valves, unexplained chest pain, a congenital heart defect, a history of heart attack or stroke, or rheumatic fever.
“Echocardiography is one of the most useful tools we have in cardiovascular research; however, it has historically been very hard to deliver in rural communities,” said study author Sanjana Ravi, M.D., an internal medicine and pediatrics resident at the Duke University School of Medicine in Durham, North Carolina. “The conventional model depends on an expert sonographer working in a hospital setting or imaging center, which can be limited in rural areas. There is also a shortage of cardiovascular imaging specialists in these regions to review and evaluate images, as well as clinicians to share results with patients.”
The current study described how a quality assurance program, including expert review at the Duke Clinical Research Institute Imaging Core Laboratory, supported non-sonographer health care staff in performing AI-guided echocardiography in a mobile examination unit in rural areas. The research is part of the large RURAL (Risk Underlying Rural Areas Longitudinal) study.
What are the study’s main findings?
“We were surprised at how quickly and well the nurses and CT technologists who had never done a heart ultrasound were able to adapt to this technology and produce quality images for review by experts,” Ravi said. “With real-time AI guidance and a rigorous quality-control system behind it, a nurse or CT technologist in a mobile unit can produce heart images good enough for research and good enough to flag serious heart problems that need follow-up, bringing the imaging to the community rather than asking the community to travel to it.”
Lee H. Schwamm, M.D., FAHA, a member of the American Heart Association’s volunteer committee on AI and Technology Innovation, said, “1 in 5 Americans lives in a rural area, which limits their access to critical diagnostic testing and specialty care. In this hybrid model, community-based non-experts were able to create a human-AI partnership with the acquisition software to enable the capture of echocardiogram images that could be read by off-site experts. This novel approach brings heart imaging to local communities and truly meets people where they are. If confirmed in further studies, this approach could serve as a model for other specialties and diagnostic modalities.” Schwamm, who was not involved in this study, is also senior vice president and chief digital health officer of the Yale New Haven Health System and associate dean of digital strategy and transformation at Yale School of Medicine.
Study details, background, design and limitations:
Co-authors, disclosures and funding sources are listed in the abstract. Gerald S. Bloomfield, M.D., M.P.H., is the study’s principal investigator and is an associate professor of medicine at the Duke University School of Medicine.
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