AI tool shows promise in diagnosing advanced heart failure

"Applying artificial intelligence techniques to cardiac ultrasound data may make it easier to identify patients with advanced heart failure, a new study has found. The study [...] offers the prospect of better care for many thousands of patients who may be overlooked due to the difficulty of diagnosing their condition.

Advanced heart failure is currently detected through cardiopulmonary exercise testing (CPET), which requires specialized equipment and trained staff and is typically only available at large medical centers. Due in part to this diagnostic bottleneck, only a few of the estimated 200,000 people in the United States with advanced heart failure get appropriate care each year.

In the new study [...] the researchers tested a novel AI-powered method that may remove this bottleneck. The new method predicts with high accuracy the most important CPET measure, peak oxygen consumption (peak VO2), using much more easily obtainable ultrasound images of the patient's heart plus the patient's electronic health records.

"This opens up a promising pathway for more efficient assessment of patients with advanced heart failure using data sources that are already embedded in routine care," said study senior author Dr. Fei Wang, the associate dean for AI and data science and the Frances and John L. Loeb Professor of Medical Informatics at Weill Cornell Medicine."