NCP: a module responsible for converting clinical judgments written in spanish natural language into a JSON format with the most important fields for analysis and data mining.
Acronyms are only expanded if they are known link and do not conflict with other words. The main objective is to correct spelling errors to improve network results.
This is done using the Prodigy tool from Explosion.
NER models, fine-tuned from a pre-trained model.
Two models:
Two phases:
Definitive terms from the database.
python test.py
python setup.py sdist
see Makefile file
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}
}