BRIGHT NER: EDS-NLP (CamemBERT + CRF) fine-tuned for dates_outcomes

Description

This is a EDS-NLP (CamemBERT + CRF) architecture fine-tuned to extract clinical neuro-oncology entities related to the dates_outcomes semantic group. It was trained on a synthetic dataset generated for the properly de-identified BRIGHT project dataset (see the generated_data folder in the primary repository).

This model repository was specifically designed to fit within the bright_db overarching namespace.

Fields

It extracts the following fields (described in French):

  • date_chir: Date intervention neurochirurgicale ou résection
  • date_rcp: Date réunion concertation pluridisciplinaire
  • dn_date: Date dernières nouvelles ou dernier suivi
  • date_deces: Date décès patient (seulement si décédé)
  • date_1er_symptome: Date apparition premiers symptômes
  • exam_radio_date_decouverte: Date premier examen découvrant la tumeur
  • date_progression: Date récidive/progression
  • survie_globale: Durée survie en mois
  • infos_deces: Circonstances décès

Performance on Validation Set

Aggregates:

  • Macro F1: 0.3203 (Precision: 0.3367, Recall: 0.3229)
  • Micro F1: 0.7421 (Precision: 0.7662, Recall: 0.7195)

Per-Label Breakdowns:

Label Precision Recall F1
date_chir 0.1429 0.2500 0.1818
date_rcp 0.9211 0.8974 0.9091
dn_date 0.0000 0.0000 0.0000
date_deces 0.0000 0.0000 0.0000
date_1er_symptome 0.0000 0.0000 0.0000
exam_radio_date_decouverte 0.1667 0.3333 0.2222
date_progression 0.0000 0.0000 0.0000
survie_globale 1.0000 0.6250 0.7692
infos_deces 0.8000 0.8000 0.8000

Usage

# Inference Code
import edsnlp

nlp = edsnlp.load("raphael-r/bright-eds-dates_outcomes")
doc = nlp("Patient presenting with epileptic seizures...")

for ent in doc.ents:
    print(ent.text, "=>", ent.label_)
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