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--- |
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tags: |
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- echocardiogram |
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- arxiv:2408.06930 |
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- medical |
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language: |
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- nl |
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license: gpl-3.0 |
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model-index: |
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- name: Echocardiogram_MitralRegurgitation_reduced |
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results: |
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- task: |
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type: text-classification |
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dataset: |
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type: test |
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name: internal test set |
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metrics: |
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- name: Macro f1 |
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type: f1 |
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value: 0.968 |
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verified: false |
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- name: Macro precision |
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type: precision |
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value: 0.964 |
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verified: false |
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- name: Macro recall |
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type: recall |
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value: 0.972 |
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verified: false |
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pipeline_tag: text-classification |
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metrics: |
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- f1 |
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- precision |
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- recall |
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--- |
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# Description |
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This model is a [MedRoBERTa.nl](https://huggingface.co/CLTL/MedRoBERTa.nl) model finetuned on Dutch echocardiogram reports sourced from Electronic Health Records. |
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The publication associated with the span classification task can be found at https://arxiv.org/abs/2408.06930. |
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The config file for training the model can be found at https://github.com/umcu/echolabeler. |
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# Minimum working example |
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```python |
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from transformer import pipeline |
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``` |
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```python |
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le_pipe = pipeline(model="UMCU/Echocardiogram_MitralRegurgitation_reduced") |
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document = "Lorem ipsum" |
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results = le_pipe(document) |
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``` |
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# Label Scheme |
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<details> |
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<summary>View label scheme</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`reduced`** | `No label`, `Normal`, `Not Normal` | |
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</details> |
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Here, for the reduced labels `Present` means that for *any one or multiple* of the pathologies we have a positive result. |
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Here, for the pathologies we have |
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<details> |
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<summary>View pathologies</summary> |
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| Annotation | Pathology | |
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| --- | --- | |
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| pe | Pericardial Effusion | |
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| wma | Wall Motion Abnormality | |
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| lv_dil | Left Ventricle Dilation | |
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| rv_dil | Right Ventricle Dilation | |
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| lv_syst_func | Left Ventricle Systolic Dysfunction | |
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| rv_syst_func | Right Ventricle Systolic Dysfunction | |
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| lv_dias_func | Diastolic Dysfunction | |
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| aortic_valve_native_stenosis | Aortic Stenosis | |
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| mitral_valve_native_regurgitation | Mitral valve regurgitation | |
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| tricuspid_valve_native_regurgitation | Tricuspid regurgitation | |
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| aortic_valve_native_regurgitation | Aortic Regurgitation | |
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</details> |
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Note: `lv_dias_func` should have been `dias_func`.. |
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# Intended use |
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The model is developed for *document* classification of Dutch clinical echocardiogram reports. |
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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*. |
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# Data |
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The model was trained on approximately 4,000 manually annotated echocardiogram reports from the University Medical Centre Utrecht. |
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The training data was anonymized before starting the training procedure. |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `Echocardiogram_MitralRegurgitation_reduced` | |
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| **Version** | `1.0.0` | |
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| **transformers** | `>=4.40.0` | |
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| **Default Pipeline** | `pipeline`, `text-classification` | |
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| **Components** | `RobertaForSequenceClassification` | |
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| **License** | `cc-by-sa-4.0` | |
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| **Author** | [Bram van Es]() | |
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# Contact |
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If you are having problems with this model please add an issue on our git: https://github.com/umcu/echolabeler/issues |
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# Usage |
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If you use the model in your work please use the following referral; https://doi.org/10.48550/arXiv.2408.06930 |
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# References |
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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 |