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?
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.
This diagnostic signature enables discrimination of HFpEF from non-cardiac dyspnea or HFrEF from EHR and can assist in the diagnostic evaluation in patients with unexplained dyspnea. This approach will enable identification of HFpEF patients who may then benefit from new evidence-based therapies.
Farajidavar et al. (Sun,) studied this question.