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README.md
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license: apache-2.0
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---
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# German Medical NER
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- **Primary Use Case**: This model is designed to extract medical entities such as symptoms, diagnostic tests, and treatments from clinical text in the German language.
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- **Applications**: Suitable for healthcare professionals, clinical data analysis, and research into medical text processing.
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- **Supported Entity Types**:
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- `PROBLEM
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- `TEST`: Diagnostic procedures and laboratory tests.
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- `TREATMENT`: Medications, therapies, and other medical interventions.
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---
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license: apache-2.0
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datasets:
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- rigonsallauka/german_ner_dataset
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language:
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- de
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metrics:
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- f1
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- precision
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- recall
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- confusion_matrix
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base_model:
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- google-bert/bert-base-cased
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pipeline_tag: token-classification
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tags:
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- NER
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- medical
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- symptom
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- extraction
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- german
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---
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# German Medical NER
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- **Primary Use Case**: This model is designed to extract medical entities such as symptoms, diagnostic tests, and treatments from clinical text in the German language.
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- **Applications**: Suitable for healthcare professionals, clinical data analysis, and research into medical text processing.
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- **Supported Entity Types**:
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- `PROBLEM`
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: Diseases, symptoms, and medical conditions.
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- `TEST`: Diagnostic procedures and laboratory tests.
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- `TREATMENT`: Medications, therapies, and other medical interventions.
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