GDEMO-HAT: Knowledge-guided Medical Text Classification Using Heterogeneous Graph-based Dependency Modeling with Hierarchical Attention-Reference-Cited by-同舟云学术

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GDEMO-HAT: Knowledge-guided Medical Text Classification Using Heterogeneous Graph-based Dependency Modeling with Hierarchical Attention

Published:2023-10-27 Issue: Volume:5 Page:47-51
ISSN:
Container-title:2023 IEEE 3rd International Conference on Data Science and Computer Application (ICDSCA)
language:
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Author:

Zhou Yunfan¹,Chen Hao¹,Li Ying²,Sun Xuxue³,Zeng Hao³,Qin Aihong³,Ma Tongqing³,Shen Shanshan⁴

Affiliation:

1. Zhejiang University,Polytechnic Institute,Hangzhou,China

2. Zhejiang University,College of Computer Science,Hangzhou,China

3. University of Zhejiang,College of Media Engineering Communication,Hangzhou,China

4. Zhejiang University,Zhejiang Hospital,Hangzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391852/10392291/10392796.pdf?arnumber=10392796

Reference20 articles.

1. Classification of neurologic outcomes from medical notes using natural language processing

2. A Novel Neural Network-Based Method for Medical Text Classification

3. Clinical Text Data in Machine Learning: Systematic Review

4. Research on Medical Text Classification Based on Improved Capsule Network

5. Medical text classification based on convolutional neural network: A review[J];Yahia;International Journal of Science and Business,2021

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