Using artificial intelligence in angiogram analysis can broaden diagnostic abilities and improve clinical decision-making, according to new research presented May 2 in Long Beach, Calif., at the Society for Cardiovascular Angiography and Interventions' Scientific Sessions 2024.
Mohamad Alkhouli, MD, a scientist from Rochester, Minn.-based Mayo Clinic, led the study which used machine-learning techniques to expand the range of data that could be observed from a traditional angiogram, according to the news release. The machine learning capabilities were trained using data from more than 20,000 angiograms that were performed at the Mayo Clinic between 2016 and 2021.
The AI was successful in predicting left ventricular ejection fraction, left ventricular filling pressures, right ventricular dysfunction, and cardiac index, proving that it was capable of producing data and information from the angiograms that would have normally required additional testing to extract.
"Traditional diagnostic tools in cardiovascular medicine harbor vast information, but much remains underutilized," said Dr. Alkhouli. "This study truly shows us AI's prowess in revealing insights beyond what the human eye can see."