A large language model based pipeline for extracting information from patient complaint and anamnesis in clinical notes for severity assessment

A large language model based pipeline for extracting information from patient complaint and anamnesis in clinical notes for severity assessment

Abstract Identifying patients with critical illness in emergency departments (EDs) is an ongoing challenge, partly due to the limited information available at the time of admission. The clinical notes in patient records have already received attention for the value of improving prediction. Recent la...

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Bibliographic Details
Main Authors: Hui Gao, Kaipeng Wang, Yuan Yuan, Yueguo Wang, Qingyuan Liu, Yulan Wang, Jian Sun, Wenwen Wang, Huanli Wang, Shusheng Zhou, Kui Jin, Mengping Zhang, Yinglei Lai
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Large language model
Emergency department
Triage
In-context learning
Retrieval-augmented generation
Online Access:https://doi.org/10.1038/s41598-025-07649-4
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https://doi.org/10.1038/s41598-025-07649-4

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