New insights from the AI-ENCODE study showed artificial intelligence (AI) successfully allowed the automated extraction of key functional and physiological data from routine angiograms.
May 3 2024Society for Cardiovascular Angiography and Interventions New insights from the AI-ENCODE study showed artificial intelligence successfully allowed the automated extraction of key functional and physiological data from routine angiograms. The late-breaking results were presented today at the Society for Cardiovascular Angiography & Interventions 2024 Scientific Sessions.
The AI-ENCODE study leveraged advanced machine-learning techniques to expand the range of data obtained from routine coronary angiograms. Using a library of more than 20,000 angiograms performed at the Mayo Clinic from 2016 to 2021, the study team developed and validated multiple AI algorithms to extract data on left and right ventricular function, intracardiac filling pressures, and cardiac index from one to two angiographic videos.
Traditional diagnostic tools in cardiovascular medicine harbor vast information, but much remains underutilized. The AI-ENCODE project proved that AI can be leveraged to unlock and deliver a broader, more meaningful spectrum of clinical findings from existing angiograms. This study truly shows us AI's prowess in revealing insights beyond what the human eye can see. It is important that we leverage AI's capabilities as a diagnostic tool to provide the best possible for our patients.
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