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raphael-r/
bright-eds-dates_outcomes

Name: bright-eds-dates_outcomes
Availability: InStock

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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

python

# 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_)