Back to search

Article

Accelerating metadata annotation in collaborative research centers: A hybrid AI workflow for biomedical entities

2026-03-30

Abstract excerpt

<title>Abstract</title> <p>Background Collaborative Research Centers rely on FAIR-compliant, richly structured metadata, yet manual annotation is a major bottleneck. We implemented an AI- and search-augmented large language model (LLM) workflow within a local research data management system to pre-annotate biomedical entities, using human-in-the-loop verification to ensure data quality. Methods The pipeline use...

Topics

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

Identifiers and source

Literature Corpus work
798716e4-cd3e-5fa3-ac2f-d142aec2ffd2
DOI
10.21203/rs.3.rs-9231981/v1
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.
Accelerating metadata annotation in collaborative research centers: A hybrid AI workflow for biomedical entitiesDOI 10.21203/rs.3.rs-9231981/v1
Select a neighboring publication to make it the new centre.