|
--- |
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tags: |
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- spacy |
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- token-classification |
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language: |
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- en |
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license: mit |
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model-index: |
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- name: en_core_med7_trf |
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results: |
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- task: |
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name: NER |
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type: token-classification |
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metrics: |
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- name: NER Precision |
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type: precision |
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value: 0.8822157434 |
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- name: NER Recall |
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type: recall |
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value: 0.925382263 |
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- name: NER F Score |
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type: f_score |
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value: 0.9032835821 |
|
--- |
|
| Feature | Description | |
|
| --- | --- | |
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| **Name** | `en_core_med7_trf` | |
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| **Version** | `3.4.2.1` | |
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| **spaCy** | `>=3.4.2,<3.5.0` | |
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| **Default Pipeline** | `transformer`, `ner` | |
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| **Components** | `transformer`, `ner` | |
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| **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) | |
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| **Sources** | n/a | |
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| **License** | `MIT` | |
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| **Author** | [Andrey Kormilitzin](https://www.kormilitzin.com/) | |
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|
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### Label Scheme |
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|
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<details> |
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|
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<summary>View label scheme (7 labels for 1 components)</summary> |
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|
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| Component | Labels | |
|
| --- | --- | |
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| **`ner`** | `DOSAGE`, `DRUG`, `DURATION`, `FORM`, `FREQUENCY`, `ROUTE`, `STRENGTH` | |
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|
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</details> |
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|
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### Accuracy |
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|
|
| Type | Score | |
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| --- | --- | |
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| `ENTS_F` | 90.33 | |
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| `ENTS_P` | 88.22 | |
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| `ENTS_R` | 92.54 | |
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| `TRANSFORMER_LOSS` | 2502627.06 | |
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| `NER_LOSS` | 114576.77 | |
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|
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### BibTeX entry and citation info |
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|
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```bibtex |
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@article{kormilitzin2021med7, |
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title={Med7: A transferable clinical natural language processing model for electronic health records}, |
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author={Kormilitzin, Andrey and Vaci, Nemanja and Liu, Qiang and Nevado-Holgado, Alejo}, |
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journal={Artificial Intelligence in Medicine}, |
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volume={118}, |
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pages={102086}, |
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year={2021}, |
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publisher={Elsevier} |
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} |
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``` |
