Back to search

Article

Artificial Intelligence Enabled Phenogrouping of Heart Failure with Preserved Ejection Fraction Depicts Early and End-Stage Trajectories

2025-06-12

Abstract excerpt

<h4>Background</h4> Heart failure with preserved ejection fraction is challenging to diagnose, precluding the initiation of prognostic medications. A deeper understanding of HFpEF phenotypes and trajectories could address this, however previous studies analyzed trial cohorts, limiting generalizability. Here we apply artificial intelligence (AI) algorithms to longitudinal electronic health record data (EHR) to char...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
f08b8d6d-9925-578e-b582-b7fcd823e834
DOI
10.1101/2025.06.09.25329306
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Artificial Intelligence Enabled Phenogrouping of Heart Failure with Preserved Ejection Fraction Depicts Early and End-Stage TrajectoriesDOI 10.1101/2025.06.09.25329306
Select a neighboring publication to make it the new centre.