Representing words as numerical vectors based on the contexts in which they appear has
become the de facto method of analyzing text with machine learning. In this paper, we …

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 …

Over a quarter of drugs that enter clinical development fail because they are ineffective.
Growing insight into genes that influence human disease may affect how drug targets and …

Artificial Intelligence federates numerous scientific fields in the aim of develo** machines
able to assist human operators performing complex treatments---most of which demand high …

Large language models (LLMs) have emerged as valuable tools for many natural language
understanding tasks. In safety-critical applications such as healthcare, the utility of these …

Motivation The amount of information available in textual format is rapidly increasing in the
biomedical domain. Therefore, natural language processing (NLP) applications are …

Objectives Named entity recognition (NER), a sequential labeling task, is one of the
fundamental tasks for building clinical natural language processing (NLP) systems. Machine …

Introduction Clinical data warehouses are often oriented toward integration and exploration
of coded data. However narrative reports are of crucial importance for translational research …

Automated approaches to measuring semantic similarity and relatedness can provide
necessary semantic context information for information retrieval applications and a number …

Abstract Measuring Semantic Textual Similarity (STS), between words/terms, sentences,
paragraph and document plays an important role in computer science and computational …