December 25, 2022BMC Cardiovascular DisordersOpen Access

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

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Why the study?

Does a machine learning diagnostic signature using multi-modality EHR data enable discrimination of HFpEF from non-cardiac dyspnea or HFrEF in patients with unexplained dyspnea?

Population

Patients with unexplained dyspnea

Authors

NFNazli FarajidavarKing's College London KOKevin O’GallagherInterventional Cardiology DBDaniel BeanKing's College London

Discussion

Member takes

Implication

May aid HFpEF discrimination from EHR in unexplained dyspnea; leaves open prospective validation before clinical use.

Structured PICO

Does a machine learning diagnostic signature using multi-modality EHR data enable discrimination of HFpEF from non-cardiac dyspnea or HFrEF in patients with unexplained dyspnea?

Population

Patients with unexplained dyspnea

Intervention

Machine learning diagnostic signature using multi-modality electronic health record (EHR) data

Outcome

Discrimination of HFpEF from non-cardiac dyspnea or HFrEF

A machine learning approach using multi-modality EHR data can assist in the diagnostic evaluation of unexplained dyspnea by discriminating HFpEF from HFrEF and non-cardiac causes.

Cite This Study

Farajidavar et al. (2022) studied this question.

synapsesocial.com/papers/69c025f295093cdbe30333c7 https://doi.org/10.1186/s12872-022-03005-w

Topics

HFrEF treatment Heart failure HFpEF management

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

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Topics

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

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Topics

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