Much of the knowledge and information needed for enabling high-quality clinical research is
stored in free-text format. Natural language processing (NLP) has been used to extract …

Abstract Biomedical Entity Linking (BEL) is the task of map** of spans of text within
biomedical documents to normalized, unique identifiers within an ontology. This is an …

Despite the widespread success of self-supervised learning via masked language models
(MLM), accurately capturing fine-grained semantic relationships in the biomedical domain …

Pretrained language models have served as important backbones for natural language
processing. Recently, in-domain pretraining has been shown to benefit various domain …

There has been a recent wave of work assessing the fairness of machine learning models in
general, and more specifically, on natural language processing (NLP) models built using …

Pretrained Masked Language Models (MLMs) have revolutionised NLP in recent years.
However, previous work has indicated that off-the-shelf MLMs are not effective as universal …

Objective This paper aims to propose knowledge-aware embedding, a critical tool for
medical term normalization. Methods We develop CODER (Cross-lingual knowledge …

Whilst there has been growing progress in Entity Linking (EL) for general language, existing
datasets fail to address the complex nature of health terminology in layman's language …

A large number of individuals are suffering from suicidal ideation in the world. There are a
number of causes behind why an individual might suffer from suicidal ideation. As the most …

Poor data quality has a direct impact on the performance of the machine learning system
that is built on the data. As a demonstrated effective approach for data quality improvement …