Label Semantic Improvement with Graph Convolutional Networks for Multi-Label Chest X-Ray Image Classification-Reference-Cited by-同舟云学术

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Label Semantic Improvement with Graph Convolutional Networks for Multi-Label Chest X-Ray Image Classification

Published:2023-11-24 Issue: Volume:arXiv preprint Page:711-717
ISSN:
Container-title:2023 13th International Conference on Information Technology in Medicine and Education (ITME)
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Author:

Cai Dachuan¹,Lu Huijuan¹,Chai Zhuijun²,Wang Renfeng³,Zhu Wenjie¹,Yao Yudong⁴

Affiliation:

1. College of Information Engineering, China Jiliang University,Hangzhou,China

2. Zhejiang Fangyuan Test Group Co., LTD,Hangzhou,China

3. Zhejiang University,Hangzhou,China

4. Stevens Institute of Technology,Department of Electrical and Computer Engineering,Hoboken,New Jersey,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10505440/10505183/10505562.pdf?arnumber=10505562

Reference26 articles.

1. Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification

2. Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance

3. Label Co-Occurrence Learning With Graph Convolutional Networks for Multi-Label Chest X-Ray Image Classification

4. RCANet: A Deep Learning Model for Thoracic Diseases Classification of Chest X-ray Images

5. Multi-Label Chest X-ray Image Classification via Semantic Similarity Graph Embedding

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