4 citations · 4 across the 1 of their papers we have counts for
2 papers
cs.CL2022★ 4 cited
Improving the Factual Correctness of Radiology Report Generation with Semantic Rewards
Jean-Benoit Delbrouck, Pierre Chambon, Christian Bluethgen +3
Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying po…
cs.CL2019
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports
Yuhao Zhang, Derek Merck, Emily Bao Tsai +2
Neural abstractive summarization models are able to generate summaries which have high overlap with human references. However, existing models are not optimized for factual correct…