A natural language processing approach to support biomedical data harmonization: Leveraging large language models.
<h4>Background</h4>Biomedical research requires large, diverse samples to produce unbiased results. Retrospective data harmonization is often used to integrate existing datasets to create these samples, but the process is labor-intensive. Automated methods for matching variables across d...
Saved in:
Main Authors: | Zexu Li, Suraj P Prabhu, Zachary T Popp, Shubhi S Jain, Vijetha Balakundi, Ting Fang Alvin Ang, Rhoda Au, Jinying Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0328262 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A natural language processing approach to support biomedical data harmonization: Leveraging large language models
by: Zexu Li, et al.
Published: (2025-01-01) -
Leveraging large language models for automated depression screening.
by: Bazen Gashaw Teferra, et al.
Published: (2025-07-01) -
Leveraging large language models for automated depression screening
by: Bazen Gashaw Teferra, et al.
Published: (2025-07-01) -
Leveraging large language models for patient-ventilator asynchrony detection
by: Lluis Blanch, et al.
Published: (2025-06-01) -
Leveraging Large Language Models for Departmental Classification of Medical Records
by: Baha Ihnaini, et al.
Published: (2025-06-01)