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 …

The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

Since the outbreak of the current pandemic in 2020, there has been a rapid growth of
published articles on COVID-19 and SARS-CoV-2, with about 10 000 new articles added …

Biomedical literature is growing rapidly, making it challenging to curate and extract
knowledge manually. Biomedical natural language processing (BioNLP) techniques that …

A wide variety of symptoms is associated with Severe Acute Respiratory Syndrome
Coronavirus 2 (SARS-CoV-2) infection, and these symptoms can overlap with other …

Motivation: The scientific literature embeds an enormous amount of relational knowledge,
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …

There has been significant recent progress in leveraging large-scale gene expression data
to develop foundation models for single-cell biology. Models such as Geneformer and …

Transformer-based neural language models have led to breakthroughs for a variety of
natural language processing (NLP) tasks. However, most models are pretrained on general …

Pretrained language models such as Bidirectional Encoder Representations from
Transformers (BERT) have achieved state-of-the-art performance in natural language …

Accurate prediction of cardiovascular disease (CVD) requires multifaceted information
consisting of not only a patient's medical history, but genomic data, symptoms, lifestyle, and …