Alvaro8gb/es_breast_cancer_ehr_ner

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

Label Scheme

View label scheme (21 labels for 1 components)

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

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:

@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}
}