license: afl-3.0
tags:
- summarization
- t5
- medical
- clinical
language: en
datasets:
- MIMIC-III
widget:
- >-
again noted is the large intraparenchymal hemorrhage in the posterior right
frontal lobe with extension into both lateral ventricles. the degree of
surrounding edema and effacement of adjacent sulci is unchanged. there is
minor contralateral shift of normal midline structures. the ventricular size
is unchanged. subarachnoid blood is now seen in the left frontal and
parietal lobes, likely due to recirculation of the ventricular blood.
- >-
a least two attempts were made at imaging, however, the study remains
severely limited by patient motion. minimal hyperdensity tracks along a left
parietal sulcus (2a:18) is equivocal for a small subarachnoid hemorhage.
there is no large mass effect detected. there is no shift of normally
midline structures. a minimally displaced zygomatic fracture is present
(2a:9). the middle ear cavities, mastoid air cells are clear. there is
extensive soft tissue swelling overlying the right frontal calvarium with
swelling extending to the right preseptal soft tissues (2a:12). there is
mild - moderate mucosal thickening within the ethmoid and maxillary sinuses
with some fluid and fluid mucosal thickening in the sphenoid sinus.
inference:
parameters:
max_length: 350
metrics:
- rouge-l
Impression section Generator For Radiology Reports 🏥
This model is is the result of participation of SINAI team in Task 1B: Radiology Report Summarization at the BioNLP workshop held on ACL 2023. The goal of this task is to foster development of automatic radiology report summarization systems and expanding their applicability by incorporating seven different modalities and anatomies in the provided data. We propose to automate the generation of radiology impressions with "sequence-to-sequence" learning that leverages the power of publicly available pre-trained models, both general domain and biomedical domain-specific. This repository provides access to our best-performing system that resulted from fine-tuning of Sci-Five base, which is T5 model trained for extra 200k steps to optimize it in the context of biomedical literature.
Results
The official evaluation results prove that adaptation of a general-domain system for biomedical literature is beneficial for the subsequent fine-tuning for radiology report summarization task. The Table below summarizes the official scores obtained by this model during the official evaluation. Team standings re available here.
| BLEU4 | ROUGUEL | BERTscore | F1-RadGraph |
|---|---|---|---|
| 017.38 | 32.32 | 55.04 | 33.96 |
System description paper and citation
The paper with the detailed description of the system will be published in the Proceedings of the 22st Workshop on Biomedical Language Processing.