tags:
- spacy
- arxiv:2408.06930
- medical
language:
- nl
license: cc-by-sa-4.0
model-index:
- name: Echocardiogram_SpanCategorizer_diastolic_dysfunction
results:
- task:
type: token-classification
dataset:
type: test
name: internal test set
metrics:
- name: Weighted f1
type: f1
value: 0.875
verified: false
- name: Weighted precision
type: precision
value: 0.902
verified: false
- name: Weighted recall
type: recall
value: 0.849
verified: false
pipeline_tag: token-classification
metrics:
- f1
- precision
- recall
Description
This model is a spaCy SpanCategorizer model trained from scratch 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
!pip install https://huggingface.co/baukearends/Echocardiogram-SpanCategorizer-diastolic-dysfunction/resolve/main/nl_Echocardiogram_SpanCategorizer_diastolic_dysfunction-any-py3-none-any.whl
import spacy
nlp = spacy.load("nl_Echocardiogram_SpanCategorizer_diastolic_dysfunction")
prediction = nlp("Op dit echo geen duidelijke WMA te zien, goede systolische L.V. functie, wel L.V.H., diastolische dysfunctie graad 1A tot 2. Geringe aortastenose en - matige -insufficientie. Geringe M.I.")
for span, score in zip(prediction.spans['sc'], prediction.spans['sc'].attrs['scores']):
print(f"Span: {span}, label: {span.label_}, score: {score[0]:.3f}")
Label Scheme
View label scheme (4 labels for 1 components)
| Component | Labels |
|---|---|
spancat |
lv_dias_func_normal, lv_dias_func_mild, lv_dias_func_severe, lv_dias_func_moderate |
Intended use
The model is developed for span classification on Dutch clinical text. Since it is a domain-specific model trained on medical data, it is meant to be used on medical NLP tasks for Dutch.
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.
| Feature | Description |
|---|---|
| Name | Echocardiogram_SpanCategorizer_diastolic_dysfunction |
| Version | 1.0.0 |
| spaCy | >=3.7.4,<3.8.0 |
| Default Pipeline | tok2vec, spancat |
| Components | tok2vec, spancat |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | cc-by-sa-4.0 |
| Author | Bauke Arends |
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