# Biomedical Entity Linking

GEBERT is a biomedical entity linking model based on PubMedBERT pre-training, enhanced with UMLS concept graph representation learning through a GAT graph encoder

KRISSBERT is a knowledge-enhanced self-supervised learning model for biomedical entity linking. It trains contextual encoders using unannotated text and domain knowledge to effectively address the diversity and ambiguity of entity names.

Biomedical entity representation model based on PubMedBERT, optimized for semantic relation capture through self-alignment pre-training

A biomedical entity representation model based on PubMedBERT, optimized for semantic relation capture through self-aligned pre-training