|
--- |
|
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 |
|
duplicated_from: kormilitzin/en_core_med7_lg |
|
--- |
|
| 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 |
|
|
|
<details> |
|
|
|
<summary>View label scheme (7 labels for 1 components)</summary> |
|
|
|
| Component | Labels | |
|
| --- | --- | |
|
| **`ner`** | `DOSAGE`, `DRUG`, `DURATION`, `FORM`, `FREQUENCY`, `ROUTE`, `STRENGTH` | |
|
|
|
</details> |
|
|
|
### 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} |
|
} |
|
``` |
