--- tags: - echocardiogram - arxiv:2408.06930 - medical language: - nl license: gpl-3.0 model-index: - name: Echocardiogram_MitralRegurgitation_reduced results: - task: type: text-classification dataset: type: test name: internal test set metrics: - name: Macro f1 type: f1 value: 0.968 verified: false - name: Macro precision type: precision value: 0.964 verified: false - name: Macro recall type: recall value: 0.972 verified: false pipeline_tag: text-classification metrics: - f1 - precision - recall --- # Description This model is a [MedRoBERTa.nl](https://huggingface.co./CLTL/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 ```python from transformer import pipeline ``` ```python le_pipe = pipeline(model="UMCU/Echocardiogram_MitralRegurgitation_reduced") document = "Lorem ipsum" results = le_pipe(document) ``` # Label Scheme
View label scheme | Component | Labels | | --- | --- | | **`reduced`** | `No label`, `Normal`, `Not Normal` |
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
View pathologies | Annotation | Pathology | | --- | --- | | pe | Pericardial Effusion | | wma | Wall Motion Abnormality | | lv_dil | Left Ventricle Dilation | | rv_dil | Right Ventricle Dilation | | lv_syst_func | Left Ventricle Systolic Dysfunction | | rv_syst_func | Right Ventricle Systolic Dysfunction | | lv_dias_func | Diastolic Dysfunction | | aortic_valve_native_stenosis | Aortic Stenosis | | mitral_valve_native_regurgitation | Mitral valve regurgitation | | tricuspid_valve_native_regurgitation | Tricuspid regurgitation | | aortic_valve_native_regurgitation | Aortic Regurgitation |
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. | Feature | Description | | --- | --- | | **Name** | `Echocardiogram_MitralRegurgitation_reduced` | | **Version** | `1.0.0` | | **transformers** | `>=4.40.0` | | **Default Pipeline** | `pipeline`, `text-classification` | | **Components** | `RobertaForSequenceClassification` | | **License** | `cc-by-sa-4.0` | | **Author** | [Bram van Es]() | # 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