Interactive dual-stream contrastive learning for radiology report generation-Reference-Cited by-同舟云学术

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Interactive dual-stream contrastive learning for radiology report generation

Published:2024-09 Issue: Volume:157 Page:104718
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Zhang Ziqi,Jiang Ailian

Publisher

Elsevier BV

Reference62 articles.

1. Deep learning approaches on image captioning: a review [J];Ghandi;ACM Comput. Surv.,2023

2. MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports [J];Johnson;Sci. Data,2019

3. Miura Y, Zhang Y, Tsai E, et al. Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation [C], in: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2021: 5288-5304.

4. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement [J];Geis;Radiology,2019

5. A survey of methods for explaining black box models [J];Guidotti;ACM Computing Surveys (CSUR),2018

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