Scalable information extraction from free text electronic health records using large language models
Abstract Background A vast amount of potentially useful information such as description of patient symptoms, family, and social history is recorded as free-text notes in electronic health records (EHRs) but is difficult to reliably extract at scale, limiting their utility in research. This study aim...
Saved in:
Main Authors: | Bowen Gu, Vivian Shao, Ziqian Liao, Valentina Carducci, Santiago Romero Brufau, Jie Yang, Rishi J. Desai |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-01-01
|
Series: | BMC Medical Research Methodology |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12874-025-02470-z |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Education as a key determinant of health: A case study from rural Anhui, China
by: Adam Mursal, et al.
Published: (2018-03-01) -
LungDiag: Empowering artificial intelligence for respiratory diseases diagnosis based on electronic health records, a multicenter study
by: Hengrui Liang, et al.
Published: (2025-01-01) -
Community-based participatory process evaluation based on the Reach, Quality Control, Fidelity, Satisfaction, and Management (RQFSM) model in Nevada: A study protocol
by: Asma Awan, et al.
Published: (2024-12-01) -
Clinical Big Data and Deep Learning: Applications, Challenges, and Future Outlooks
by: Ying Yu, et al.
Published: (2019-12-01) -
Digital Diagnostics: The Potential of Large Language Models in Recognizing Symptoms of Common Illnesses
by: Gaurav Kumar Gupta, et al.
Published: (2025-01-01)