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---
language:
- es
tags:
- NER
- named entity recognition
- biomedical
- clinical
- EHR
- spanish
- location
- geopolitical
- facility
- geographical
- transport
- community
- language
- clinical department
license: apache-2.0
metrics:
- precision
- recall
- f1
base_model:
- PlanTL-GOB-ES/bsc-bio-ehr-es
model-index:
- name: BSC-NLP4BIA/location-tagger
results:
- task:
type: token-classification
dataset:
name: MEDDOPLACE (subtrack 1)
type: MEDDOPLACE
metrics:
- name: precision (micro)
type: precision
value: 0.865
- name: recall (micro)
type: recall
value: 0.859
- name: f1 (micro)
type: f1
value: 0.862
widget:
- text: >-
El diagnóstico definitivo de nuestro paciente fue de un Adenocarcinoma de
pulmón cT2a cN3 cM1a Estadio IV (por una única lesión pulmonar
contralateral) PD-L1 90%, EGFR negativo, ALK negativo y ROS-1 negativo.
- text: >-
Durante el ingreso se realiza una TC, observándose un nódulo pulmonar en el
LII y una masa renal derecha indeterminada. Se realiza punción biopsia del
nódulo pulmonar, con hallazgos altamente sospechosos de carcinoma.
- text: >-
Trombosis paraneoplásica con sospecha de hepatocarcinoma por imagen, sobre
hígado cirrótico, en paciente con índice Child-Pugh B.
pipeline_tag: token-classification
---
# LocationTagger
## Table of contents
<details>
<summary>Click to expand</summary>
- [Model description](#model-description)
- [How to use](#how-to-use)
- [Limitations and bias](#limitations-and-bias)
- [Training](#training)
- [Evaluation](#evaluation)
- [Additional information](#additional-information)
- [Authors](#authors)
- [Contact information](#contact-information)
- [Licensing information](#licensing-information)
- [Funding](#funding)
- [Citing information](#citing-information)
- [Disclaimer](#disclaimer)
</details>
## Model description
A fine-tuned version of the [bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) model on the [MEDDOPLACE](https://doi.org/10.5281/zenodo.7707566) corpus (subtrack 1) for named geopolitical entities (GPE_NOM), generic geopolitical entities (GPE_GEN), named geographical entities (GEO_NOM), generic geographical entities (GEO_GEN), named facility entities (FAC_NOM), generic facility entities (FAC_GEN), community (COMUNIDAD), language (IDIOMA), transportation (TRANSPORTE), and clinical departments and services (DEPARTAMENTO).
For further information, check the [official website](https://temu.bsc.es/meddoplace/).
## How to use
⚠ We recommend pre-tokenizing the input text into words instead of providing it directly to the model, as this is how the model was trained. Otherwise, the results and performance might get affected.
A usage example can be found [here](https://github.com/nlp4bia-bsc/hugging-face-pipeline/blob/main/simple_inference.ipynb).
## Limitations and bias
At the time of submission, no measures have been taken to estimate the bias embedded in the model. However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. We intend to conduct research in these areas in the future, and if completed, this model card will be updated.
## Evaluation
Strict (same class, exact boundary) and overlapping (same class, some overlap) metrics for the MEDDOPLACE Subtrack 1 test set.
| | precision | recall | f_score | ov_precision | ov_recall | ov_f_score |
| ------------ | :-------: | :----: | :-----: | :----------: | :-------: | :--------: |
| COMUNIDAD | 0.895 | 0.747 | 0.814 | 0.895 | 0.747 | 0.814 |
| DEPARTAMENTO | 0.898 | 0.897 | 0.897 | 0.935 | 0.934 | 0.935 |
| FAC_GEN | 0.876 | 0.866 | 0.871 | 0.911 | 0.900 | 0.905 |
| FAC_NOM | 0.552 | 0.681 | 0.610 | 0.724 | 0.894 | 0.800 |
| GEO_GEN | 0.745 | 0.859 | 0.798 | 0.776 | 0.894 | 0.831 |
| GEO_NOM | 0.400 | 0.400 | 0.400 | 0.500 | 0.500 | 0.500 |
| GPE_GEN | 0.851 | 0.866 | 0.858 | 0.930 | 0.946 | 0.938 |
| GPE_NOM | 0.902 | 0.868 | 0.885 | 0.936 | 0.900 | 0.917 |
| IDIOMA | 0.739 | 0.739 | 0.739 | 0.913 | 0.913 | 0.913 |
| TRANSPORTE | 0.878 | 0.825 | 0.851 | 0.926 | 0.870 | 0.897 |
| **micro avg** | **0.865** | **0.859** | **0.862** | **0.909** | **0.903** | **0.906** |
## Additional information
### Authors
NLP4BIA team at the Barcelona Supercomputing Center ([email protected]).
### Contact information
jan.rodriguez [at] bsc.es
### Licensing information
[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
### Funding
TBD
### Citing information
Please cite the following works:
### Disclaimer
The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions.
When third parties deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence.
---
Los modelos publicados en este repositorio tienen una finalidad generalista y están a disposición de terceros. Estos modelos pueden tener sesgos y/u otro tipo de distorsiones indeseables.
Cuando terceros desplieguen o proporcionen sistemas y/o servicios a otras partes usando alguno de estos modelos (o utilizando sistemas basados en estos modelos) o se conviertan en usuarios de los modelos, deben tener en cuenta que es su responsabilidad mitigar los riesgos derivados de su uso y, en todo caso, cumplir con la normativa aplicable, incluyendo la normativa en materia de uso de inteligencia artificial. |