---
tags:
- spacy
- token-classification
language:
- es
license: mit
model-index:
- name: es_BreastCancerNER
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.9245630175
    - name: NER Recall
      type: recall
      value: 0.9396914446
    - name: NER F Score
      type: f_score
      value: 0.9320658474
---
Breast Cancer Diagnosis NER model

| Feature | Description |
| --- | --- |
| **Name** | `es_BreastCancerNER` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.5.0,<3.6.0` |
| **Default Pipeline** | `transformer`, `ner` |
| **Components** | `transformer`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | `mit` |
| **Author** | [Álvaro García Barragán](https://huggingface.co/Alvaro8gb/es_BreastCancerNER) |

### Label Scheme

<details>

<summary>View label scheme (21 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `CANCER_CONCEPT`, `CANCER_EXP`, `CANCER_GRADE`, `CANCER_INTRTYPE`, `CANCER_LOC`, `CANCER_MET`, `CANCER_REC`, `CANCER_STAGE`, `CANCER_SUBTYPE`, `CANCER_TYPE`, `DATE`, `IMPLICIT_DATE`, `MOLEC_MARKER`, `SURGERY`, `TNM`, `TRAT`, `TRAT_DRUG`, `TRAT_FREQ`, `TRAT_INTERVAL`, `TRAT_QUANTITY`, `TRAT_SHEMA` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 93.21 |
| `ENTS_P` | 92.46 |
| `ENTS_R` | 93.97 |
| `TRANSFORMER_LOSS` | 45014.63 |
| `NER_LOSS` | 1216054.67 |



## Citation
If you use our work in your research, please cite it as follows:

```bibtex
@INPROCEEDINGS{garcia-barraganCBMS2023,
  author={García-Barragán, Alvaro and Solarte-Pabón, Oswaldo and Nedostup, Georgiy and Provencio, Mariano and Menasalvas, Ernestina and Robles, Victor},
  booktitle={2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)},
  title={Structuring Breast Cancer Spanish Electronic Health Records Using Deep Learning},
  year={2023},
  pages={404-409},
  keywords={Natural Language Processing (NLP), Information extraction, Deep Learning, Breast cancer.},
  doi={10.1109/CBMS58004.2023.00252}
}
```