Diagnostic signature for heart failure with preserved ejection fraction (HFpEF): a machine learning approach using multi-modality electronic health record data

Diagnostic signature for heart failure with preserved ejection fraction (HFpEF): a machine learning approach using multi-modality electronic health record data

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is thought to be highly prevalent yet remains underdiagnosed. Evidence-based treatments are available that increase quality of life and decrease hospitalization. We sought to develop a data-driven diagnostic model to predict ...

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Bibliographic Details
Main Authors: Nazli Farajidavar, Kevin O’Gallagher, Daniel Bean, Adam Nabeebaccus, Rosita Zakeri, Daniel Bromage, Zeljko Kraljevic, James T. H. Teo, Richard J. Dobson, Ajay M. Shah
Format: Article
Language:English
Published: BMC 2022-12-01
Series:BMC Cardiovascular Disorders
Subjects:
HFpEF
Machine learning
Dyspnea
Online Access:https://doi.org/10.1186/s12872-022-03005-w

Internet

https://doi.org/10.1186/s12872-022-03005-w

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