A Knowledge Recall Framework for Biomedical Abbreviation Disambiguation Using Pre-Trained Transformer Models

Background: The inherent polysemy of abbreviations in biomedical text presents a persistent challenge in natural language processing systems for Word Sense Disambiguation. Current approaches often struggle to fully leverage the vast, latent knowledge embedded within pre-trained transformer models. M...

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Bibliographic Details

Main Authors:	Ghada M. Farouk, Sally S. Ismail, Mostafa M. Aref
Format:	Artigo
Language:	Inglês
Published:	IEEE 2026-01-01
Series:	IEEE Access
Subjects:	Biomedical informatics deep learning decision support systems knowledge representation natural language processing ontology
Online Access:	https://ieeexplore.ieee.org/document/11408810/
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