license: mit
inference:
parameters:
aggregation_strategy: average
language:
- pt
pipeline_tag: token-classification
tags:
- medialbertina-ptpt
- deberta
- portuguese
- european portuguese
- medical
- clinical
- healthcare
- NER
- Named Entity Recognition
- IE
- Information Extraction
widget:
- text: >-
Durante a cirurgia ortopédica para corrigir a fratura no tornozelo, os
sinais vitais do utente, incluindo a pressão arterial, com leitura de
120/87 mmHg, a frequência cardíaca, de 80 batimentos por minuto, e SpO2 a
98%, foram monitorizados. Após a cirurgia o utente apresentava dor
intensa no local e inchaço no tornozelo, mas os resultados dos exames de
radiografia revelaram uma recuperação satisfatória.
example_title: Example 1
- text: >-
Durante o procedimento endoscópico, foram encontrados pólipos no cólon do
paciente.
example_title: Example 2
- text: Foi recomendada aspirina de 500mg a cada 4 horas, durante 3 dias.
example_title: Example 3
- text: >-
Após as sessões de fisioterapia o paciente apresenta recuperação de
mobilidade.
example_title: Example 4
- text: >-
O paciente está em Quimioterapia com uma dosagem específica de Cisplatina
para o tratamento do cancro do pulmão.
example_title: Example 5
- text: Monitorização da Freq. cardíaca com 90 bpm. P Arterial de 120-80 mmHg
example_title: Example 6
- text: >-
A ressonância magnética da utente revelou uma ruptura no menisco lateral
do joelho.
example_title: Example 7
- text: >-
A paciente foi diagnosticada com esclerose múltipla e iniciou terapia com
imunomoduladores.
MediAlbertina
The first publicly available medical language models trained with real European Portuguese data.
MediAlbertina is a family of encoders from the Bert family, DeBERTaV2-based, resulting from the continuation of the pre-training of PORTULAN's Albertina models with Electronic Medical Records shared by Portugal's largest public hospital.
Like its antecessors, MediAlbertina models are distributed under the MIT license.
Model Description
MediAlbertina PT-PT 900M NER was created through fine-tuning of MediAlbertina PT-PT 900M on real European Portuguese EMRs that have been hand-annotated for the following entities:
- Diagnostico
- Sintoma
- Medicamento
- Dosagem
- ProcedimentoMedico
- SinalVital
- Resultado
- Progresso
MediAlbertina PT-PT 900M NER achieved superior results to the same adaptation made on a non-medical Portuguese language model, demonstrating the effectiveness of this domain adaptation, and its potential for medical AI in Portugal.
| Model | NER single-model | NER multi-models | Assertion Status |
|---|---|---|---|
| F1-score | F1-score | F1-score | |
| albertina-900m-portuguese-ptpt-encoder | 0.813 | 0.811 | 0.687 |
| medialbertina_pt-pt_900m | 0.832 | 0.848 | 0.755 |
Data
MediAlbertina PT-PT 900M NER was fine-tuned on more than 10k hand-annotated entities from more than a thousand fully anonymized medical sentences from Portugal's largest public hospital. This data was acquired under the framework of the FCT project DSAIPA/AI/0122/2020 AIMHealth-Mobile Applications Based on Artificial Intelligence.
How to use
from transformers import pipeline
ner_pipeline = pipeline('ner', model='portugueseNLP/medialbertina_pt-pt_900m_NER', aggregation_strategy='average')
sentence = 'Durante o procedimento endoscópico, foram encontrados pólipos no cólon do paciente.'
entities = ner_pipeline(sentence)
for entity in entities:
print(f"{entity['entity_group']} - {sentence[entity['start']:entity['end']]}")
Citation
MediAlbertina is developed by a joint team from ISCTE-IUL, Portugal, and Select Data, CA USA. For a fully detailed description, check the respective publication:
In publishing process. Reference will be added soon.
Please use the above cannonical reference when using or citing this model.