The discovery and development of new medicines is expensive, time-consuming, and often
inefficient, with many failures along the way. Powered by artificial intelligence (AI), language …

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

Abstract PubTator Central (https://www. ncbi. nlm. nih. gov/research/pubtator/) is a web
service for viewing and retrieving bioconcept annotations in full text biomedical articles …

Motivation: Text mining is increasingly used to manage the accelerating pace of the
biomedical literature. Many text mining applications depend on accurate named entity …

Motivation: Despite the central role of diseases in biomedical research, there have been
much fewer attempts to automatically determine which diseases are mentioned in a text …

Developing high-performance entity normalization algorithms that can alleviate the term
variation problem is of great interest to the biomedical community. Although deep learning …

Biomedical named entities often play important roles in many biomedical text mining tools.
However, due to the incompleteness of provided synonyms and numerous variations in their …

Chemical compounds and drugs are an important class of entities in biomedical research
with great potential in a wide range of applications, including clinical medicine. Locating …

The automatic recognition of gene names and their associated database identifiers from
biomedical text has been widely studied in recent years, as these tasks play an important …

The amount of biomedical literature is vast and growing quickly, and accurate text mining
techniques could help researchers to efficiently extract useful information from the literature …