activity
20202022
most citedRadGraph: Extracting Clinical Entities and Relations from Radiology Reports

68 citations · 146 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV202258 cited

RoentGen: Vision-Language Foundation Model for Chest X-ray Generation

Pierre Chambon, Christian Bluethgen, Jean-Benoit Delbrouck +7

Multimodal models trained on large natural image-text pair datasets have exhibited astounding abilities in generating high-quality images. Medical imaging data is fundamentally dif…

cs.CL20224 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.CL202168 cited

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Saahil Jain, Ashwin Agrawal, Adriel Saporta +9

Extracting structured clinical information from free-text radiology reports can enable the use of radiology report information for a variety of critical healthcare applications. In…

cs.CV2021

Predicting post-operative right ventricular failure using video-based deep learning

Rohan Shad, Nicolas Quach, Robyn Fong +17

Non-invasive and cost effective in nature, the echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves. Despite progressive improvements over the…

cs.CL202016 cited

Biomedical and Clinical English Model Packages in the Stanza Python NLP Library

Yuhao Zhang, Yuhui Zhang, Peng Qi +2

We introduce biomedical and clinical English model packages for the Stanza Python NLP library. These packages offer accurate syntactic analysis and named entity recognition capabil…