Machine learning analysis of left ventricular function to characterize heart failure with preserved ejection fraction

Sanchez Martinez, Sergio; Duchateau, Nicolas; Erdei, Tamas; Kunszt, Gabor; Aakhus, Svend; Degiovanni, Anna; Marino, Paolo; Carluccio, Erberto; Piella Fenoy, Gemma; Fraser, Alan G.; Bijnens, Bart

doi:http://dx.doi.org/10.1161/CIRCIMAGING.117.007138

Machine learning analysis of left ventricular function to characterize heart failure with preserved ejection fraction

Citation

Sanchez-Martinez S, Duchateau N, Erdei T, Kunszt G, Aakhus S, Degiovanni A, Marino P, Carluccio E, Piella G, Fraser AG, Bijnens BH. Machine learning analysis of left ventricular function to characterize heart failure with preserved ejection fraction. Circ Cardiovasc Imaging. 2018 Apr 16;11(4):e007138. DOI: 10.1161/CIRCIMAGING.117.007138

Abstract

Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function at rest and exercise objectively captures differences between HFpEF and healthy subjects.