e-Health CSIRO at RadSum23: Adapting a Chest X-Ray Report Generator to Multimodal Radiology Report Summarisation

Aaron Nicolson, Jason Dowling, Bevan Koopman


Abstract
We describe the participation of team e-Health CSIRO in the BioNLP RadSum task of 2023. This task aims to develop automatic summarisation methods for radiology. The subtask that we participated in was multimodal; the impression section of a report was to be summarised from a given findings section and set of Chest X-rays (CXRs) of a subject’s study. For our method, we adapted an encoder-to-decoder model for CXR report generation to the subtask. e-Health CSIRO placed seventh amongst the participating teams with a RadGraph ER F1 score of 23.9.
Anthology ID:
2023.bionlp-1.56
Volume:
The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Dina Demner-fushman, Sophia Ananiadou, Kevin Cohen
Venue:
BioNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
545–549
Language:
URL:
https://aclanthology.org/2023.bionlp-1.56
DOI:
10.18653/v1/2023.bionlp-1.56
Bibkey:
Cite (ACL):
Aaron Nicolson, Jason Dowling, and Bevan Koopman. 2023. e-Health CSIRO at RadSum23: Adapting a Chest X-Ray Report Generator to Multimodal Radiology Report Summarisation. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 545–549, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
e-Health CSIRO at RadSum23: Adapting a Chest X-Ray Report Generator to Multimodal Radiology Report Summarisation (Nicolson et al., BioNLP 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.bionlp-1.56.pdf