Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department

Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department

Abstract Background Accurate triage is required for efficient allocation of resources and to decrease patients’ length of stay. Triage decisions are often subjective and vary by provider, leading to patients being over-triaged or under-triaged. This study developed machine learning models that incor...

Full description

Saved in:
Bibliographic Details
Main Authors: Yu-Hsin Chang, Ying-Chen Lin, Fen-Wei Huang, Dar-Min Chen, Yu-Ting Chung, Wei-Kung Chen, Charles C.N. Wang
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Emergency Medicine
Subjects:
Natural Language Processing
Triage
Emergency Department
Disposition Prediction
Machine Learning
Online Access:https://doi.org/10.1186/s12873-024-01152-1
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s12873-024-01152-1

Similar Items