@article{ART003212651},
author={Tae-Hyeong Kwon and Dae-Ho Kim and Se Young Kim and Ok-Ran Jeong},
title={Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={6},
pages={11-20}
TY - JOUR
AU - Tae-Hyeong Kwon
AU - Dae-Ho Kim
AU - Se Young Kim
AU - Ok-Ran Jeong
TI - Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 6
PB - The Korean Society Of Computer And Information
SP - 11
EP - 20
SN - 1598-849X
AB - In this study, we developed a model to support nurse decision-making using Korean nursing record data and explored methods to enhance performance by applying data augmentation techniques. Previous research primarily focused on English medical data, resulting in a lack of studies on Korean medical data. To address this gap, we utilized electronic medical record (EMR) data from abdominal surgery patients and developed a KoBERT-based model for predicting nursing actions. Additionally, we applied techniques such as up/down sampling, few-shot augmentation, back-translation, and synonym replacement to mitigate data imbalance and compared their performance. Experimental results show that the Few-shot Augmentation achieved the highest performance, confirming that data augmentation is effective in increasing the diversity of EMR data.
KW - Data Augmentation;Few-shot;Back-Translation;Synonym Replacement
DO -
UR -
ER -
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim and Ok-Ran Jeong. (2025). Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique. Journal of The Korea Society of Computer and Information, 30(6), 11-20.
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim and Ok-Ran Jeong. 2025, "Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique", Journal of The Korea Society of Computer and Information, vol.30, no.6 pp.11-20.
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim, Ok-Ran Jeong "Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique" Journal of The Korea Society of Computer and Information 30.6 pp.11-20 (2025) : 11.
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim, Ok-Ran Jeong. Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique. 2025; 30(6), 11-20.
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim and Ok-Ran Jeong. "Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique" Journal of The Korea Society of Computer and Information 30, no.6 (2025) : 11-20.
Tae-Hyeong Kwon; Dae-Ho Kim; Se Young Kim; Ok-Ran Jeong. Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique. Journal of The Korea Society of Computer and Information, 30(6), 11-20.
Tae-Hyeong Kwon; Dae-Ho Kim; Se Young Kim; Ok-Ran Jeong. Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique. Journal of The Korea Society of Computer and Information. 2025; 30(6) 11-20.
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim, Ok-Ran Jeong. Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique. 2025; 30(6), 11-20.
Tae-Hyeong Kwon, Dae-Ho Kim, Se Young Kim and Ok-Ran Jeong. "Improving Deep Learning Performance on Imbalanced Medical Data Using Natural Language Data Augmentation Technique" Journal of The Korea Society of Computer and Information 30, no.6 (2025) : 11-20.
