Back to search

Article

The Promise and Peril of Large Language Models in Digital Health: GPT-4 Personalizes Cardiovascular Patient Education but Amplifies Gender Biases

2025-11-20

Abstract excerpt

<h4>Background</h4> Gender-neutral patient education materials often overlook critical sex-based differences in cardiovascular disease (CVD). Large Language Models (LLMs) like GPT-4 offer a potential tool for personalizing health communication, but their ability to correct gender gaps without introducing new biases is unknown. <h4>Methods</h4> We identified seven publicly available English-language CVD preventio...

Topics

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

Identifiers and source

Literature Corpus work
489cb427-ffe8-526c-b2ca-4c8f689172d6
DOI
10.1101/2025.11.19.25340616
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.
The Promise and Peril of Large Language Models in Digital Health: GPT-4 Personalizes Cardiovascular Patient Education but Amplifies Gender BiasesDOI 10.1101/2025.11.19.25340616
Select a neighboring publication to make it the new centre.