Back to search

Article

Performance, Generalizability, and Fairness of a Peripheral Artery Disease Detection Model Across Patient Phenotypes and Health Systems

2026-08-22

Abstract excerpt

<h4>Background: </h4> Peripheral artery disease (PAD) is a major cause of cardiovascular events but remains underdiagnosed. Electronic health record (EHR)-based machine learning models show promise for earlier detection, but developing generalizable and fair models across diverse populations remains challenging. Methods Using the University of California Health Data Warehouse, containing EHR data from five health...

Topics

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

Identifiers and source

Literature Corpus work
6f9a1faa-bc4f-5061-94ca-1fa9d5ae86f2
DOI
10.64898/2026.08.19.26360861
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.
Performance, Generalizability, and Fairness of a Peripheral Artery Disease Detection Model Across Patient Phenotypes and Health SystemsDOI 10.64898/2026.08.19.26360861
Select a neighboring publication to make it the new centre.