Back to search

Article

Utilizing AI-Generated Plain Language Summaries to Enhance Interdisciplinary Understanding of Ophthalmology Notes: A Randomized Trial

2024-09-13

Abstract excerpt

<h4>Background: </h4> Specialized terminology employed by ophthalmologists creates a comprehension barrier for non-ophthalmology providers, compromising interdisciplinary communication and patient care. Current solutions such as manual note simplification are impractical or inadequate. Large language models (LLMs) present a potential low-burden approach to translating ophthalmology documentation into accessible la...

Topics

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

Identifiers and source

Literature Corpus work
629bece1-8f25-5bf2-8367-2a22095f2167
DOI
10.1101/2024.09.12.24313551
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.
Utilizing AI-Generated Plain Language Summaries to Enhance Interdisciplinary Understanding of Ophthalmology Notes: A Randomized TrialDOI 10.1101/2024.09.12.24313551
Select a neighboring publication to make it the new centre.