Optum at MEDIQA 2021: Abstractive Summarization of Radiology Reports using simple BART Finetuning
Ravi Kondadadi | Sahil Manchanda | Jason Ngo | Ronan McCormack
Proceedings of the 20th Workshop on Biomedical Language Processing
This paper describes experiments undertaken and their results as part of the BioNLP MEDIQA 2021 challenge. We participated in Task 3: Radiology Report Summarization. Multiple runs were submitted for evaluation, from solutions leveraging transfer learning from pre-trained transformer models, which were then fine tuned on a subset of MIMIC-CXR, for abstractive report summarization. The task was evaluated using ROUGE and our best performing system obtained a ROUGE-2 score of 0.392.