Entity-enhanced BERT for medical specialty prediction based on clinical questionnaire data.
A medical specialty prediction system for remote diagnosis can reduce the unexpected costs incurred by first-visit patients who visit the wrong hospital department for their symptoms. To develop medical specialty prediction systems, several researchers have explored clinical predictive models using...
Saved in:
Main Authors: | Soyeon Lee, Ye Ji Han, Hyun Joon Park, Byung Hoon Lee, DaHee Son, SoYeon Kim, HyeonJong Yang, TaeJun Han, EunSun Kim, Sung Won Han |
---|---|
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.0317795 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
ABioNER: A BERT-Based Model for Arabic Biomedical Named-Entity Recognition
by: Nada Boudjellal, et al.
Published: (2021-01-01) -
A BERT-BiGRU-CRF Model for Entity Recognition of Chinese Electronic Medical Records
by: Qiuli Qin, et al.
Published: (2021-01-01) -
Intraosseous Hemangioma of the Middle Turbinate Misdiagnosed As a Nasal Polyp
by: Tae Hoon Kim, et al.
Published: (2014-01-01) -
Use of the Adaptive Behaviour Dementia Questionnaire in a Down Syndrome Specialty Clinic
by: Nicolas M. Oreskovic, et al.
Published: (2025-01-01) -
Evaluation of Airborne Particulate Matter and Volatile Organic Compounds Released by Three Types of Mosquito Repellents
by: Soyeon Lee, et al.
Published: (2024-03-01)