Evaluation of BERT-Based Models on Patient Data from French Social Media.
Stud Health Technol Inform
; 316: 894-898, 2024 Aug 22.
Article
en En
| MEDLINE
| ID: mdl-39176937
ABSTRACT
With the objective of extracting new knowledge about rare diseases from social media messages, we evaluated three models on a Named Entity Recognition (NER) task, consisting of extracting phenotypes and treatments from social media messages. We trained the three models on a dataset with social media messages about Developmental and Epileptic Encephalopathies and more common diseases. This preliminary study revealed that CamemBERT and CamemBERT-bio exhibit similar performance on social media testimonials, slightly outperforming DrBERT. It also highlighted that their performance was lower on this type of data than on structured health datasets. Limitations, including a narrow focus on NER performance and dataset-specific evaluation, call for further research to fully assess model capabilities on larger and more diverse datasets.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Medios de Comunicación Sociales
Límite:
Humans
País/Región como asunto:
Europa
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2024
Tipo del documento:
Article
País de afiliación:
Francia
Pais de publicación:
Países Bajos