nav-nlp at RadSum23: Abstractive Summarization of Radiology Reports using BART Finetuning

Sri Macharla, Ashok Madamanchi, Nikhilesh Kancharla

Abstract
This paper describes the experiments undertaken and their results as part of the BioNLP 2023 workshop. We took part in Task 1B: Radiology Report Summarization. Multiple runs were submitted for evaluation from solutions utilizing transfer learning from pre-trained transformer models, which were then fine-tuned on MIMIC-III dataset, for abstractive report summarization.
Anthology ID:
2023.bionlp-1.55
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:
541–544
Language:
URL:
https://aclanthology.org/2023.bionlp-1.55
DOI:
10.18653/v1/2023.bionlp-1.55
Bibkey:
Cite (ACL):
Sri Macharla, Ashok Madamanchi, and Nikhilesh Kancharla. 2023. nav-nlp at RadSum23: Abstractive Summarization of Radiology Reports using BART Finetuning. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 541–544, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
nav-nlp at RadSum23: Abstractive Summarization of Radiology Reports using BART Finetuning (Macharla et al., BioNLP 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-1/2023.bionlp-1.55.pdf
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