UMCU / Echocardiogram_WMA_reduced

Description

This model is a MedRoBERTa.nl model finetuned on Dutch echocardiogram reports sourced from Electronic Health Records. The publication associated with the span classification task can be found at https://arxiv.org/abs/2408.06930 . The config file for training the model can be found at https://github.com/umcu/echolabeler .

Minimum working example

from transformer import pipeline

le_pipe = pipeline(model="UMCU/Echocardiogram_WMA_reduced")
document = "Lorem ipsum"
results = le_pipe(document)

Label Scheme

Here, for the reduced labels Present means that for any one or multiple of the pathologies we have a positive result.

Here, for the pathologies we have

Note: lv_dias_func should have been dias_func ..

Intended use

The model is developed for document classification of Dutch clinical echocardiogram reports. Since it is a domain-specific model trained on medical data, it is only meant to be used on medical NLP tasks for Dutch echocardiogram reports .

Data

The model was trained on approximately 4,000 manually annotated echocardiogram reports from the University Medical Centre Utrecht. The training data was anonymized before starting the training procedure.

Contact

If you are having problems with this model please add an issue on our git: https://github.com/umcu/echolabeler/issues

Usage

If you use the model in your work please use the following referral; https://doi.org/10.48550/arXiv.2408.06930

References

Paper: Bauke Arends, Melle Vessies, Dirk van Osch, Arco Teske, Pim van der Harst, René van Es, Bram van Es (2024): Diagnosis extraction from unstructured Dutch echocardiogram reports using span- and document-level characteristic classification, Arxiv https://arxiv.org/abs/2408.06930