2023
ACL
ACL 2023
e-Health CSIRO at RadSum23: Adapting a Chest X-Ray Report Generator to Multimodal Radiology Report Summarisation
Abstract
AbstractWe 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.
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Interdisciplinary Bridge
— Computer Science and Computer Vision and Deep Learning and Healthcare & Medicine and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Computer Vision > Domain-Specific > Medical Imaging
Natural Language Processing > Generation > Summarization
Healthcare & Medicine > Clinical > Medical Imaging
Computer Science > Applications > Document Analysis
Computer Vision > Core AI > Multimodal Learning
Deep Learning > Learning Types > Multi-Modal Learning