Assimilated LVEF: A Bayesian technique combining human intuition with machine measurement for sharper estimates of left ventricular ejection fraction and stronger association with outcomes Article Swipe

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Ejection fraction Cardiology Internal medicine Medicine Intuition Bayesian probability Heart failure Artificial intelligence Computer science Psychology Cognitive science

Thomas McAndrew , Björn Redfors , Aaron Crowley , Yiran Zhang , Maria Alu , Matthew Finn , Ariel Furer , Shmuel Chen , Géraldine Ong , Daniel Burkhoff , Ori Ben‐Yehuda , Wael A. Jaber , Rebecca T. Hahn , Martin B. Leon ·

YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1805.02764 · OA: W2802000910

The cardiologist's main tool for measuring systolic heart failure is left ventricular ejection fraction (LVEF). Trained cardiologist's report both a visual and machine-guided measurement of LVEF, but only use this machine-guided measurement in analysis. We use a Bayesian technique to combine visual and machine-guided estimates from the PARTNER-IIA Trial, a cohort of patients with aortic stenosis at moderate risk treated with bioprosthetic aortic valves, and find our combined estimate reduces measurement errors and improves the association between LVEF and a 1-year composite endpoint.