Learning to Summarize Chinese Radiology Findings With a Pre-Trained Encoder

Author:

Jiang Zuowei1ORCID,Cai Xiaoyan2ORCID,Yang Libin3ORCID,Gao Dehong3ORCID,Zhao Wei4ORCID,Han Junwei1ORCID,Liu Jun5ORCID,Shen Dinggang6ORCID,Liu Tianming7ORCID

Affiliation:

1. School of Automation, Northwestern Polytechnical University, China

2. School of Automation, Northwestern Polytechnical University, Xi'an, China

3. School of Cybersecurity, Northwestern Polytechnical University, Xi'an, China

4. Department of Radiology, The Second Xiangya Hospital, Central South University, China

5. Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China

6. School of Biomedical Engineering, ShanghaiTech University, Shanghai, China

7. Department of Computer Science, The University of Georgia, Athens, GA, USA

Funder

National Natural Science Foundation of China

Project of Humanities and Social Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Reference64 articles.

1. Biomedical-domain pre-trained language model for extractive summarization

2. Machine translation and the evaluation of its quality;mau?ec;Proc 22nd Int Conf Text Speech Dialogue,0

3. StarSum: A Star Architecture Based Model for Extractive Summarization

4. Rouge: A package for automatic evaluation of summaries;lin;Text Summarization Branches Out,2004

5. Automatic text summarization: A comprehensive survey;el-kassas;Expert Syst Appl,2021

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