--- tags: - spacy - token-classification language: - en license: mit model-index: - name: en_core_med7_lg results: - task: name: NER type: token-classification metrics: - name: NER Precision type: precision value: 0.8649613325 - name: NER Recall type: recall value: 0.8892966361 - name: NER F Score type: f_score value: 0.876960193 --- | Feature | Description | | --- | --- | | **Name** | `en_core_med7_lg` | | **Version** | `3.4.2.1` | | **spaCy** | `>=3.4.2,<3.5.0` | | **Default Pipeline** | `tok2vec`, `ner` | | **Components** | `tok2vec`, `ner` | | **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) | | **Sources** | n/a | | **License** | `MIT` | | **Author** | [Andrey Kormilitzin](https://www.kormilitzin.com/) | ### Label Scheme
View label scheme (7 labels for 1 components) | Component | Labels | | --- | --- | | **`ner`** | `DOSAGE`, `DRUG`, `DURATION`, `FORM`, `FREQUENCY`, `ROUTE`, `STRENGTH` |
### Accuracy | Type | Score | | --- | --- | | `ENTS_F` | 87.70 | | `ENTS_P` | 86.50 | | `ENTS_R` | 88.93 | | `TOK2VEC_LOSS` | 226109.53 | | `NER_LOSS` | 302222.55 | ### BibTeX entry and citation info ```bibtex @article{kormilitzin2021med7, title={Med7: A transferable clinical natural language processing model for electronic health records}, author={Kormilitzin, Andrey and Vaci, Nemanja and Liu, Qiang and Nevado-Holgado, Alejo}, journal={Artificial Intelligence in Medicine}, volume={118}, pages={102086}, year={2021}, publisher={Elsevier} } ```