Cancer is a malignant disease that has caused millions of human deaths. Its study has a
long history of well over 100years. There have been an enormous number of publications on …

Motivation State-of-the-art biomedical named entity recognition (BioNER) systems often
require handcrafted features specific to each entity type, such as genes, chemicals and …

A huge amount of important biomedical information is hidden in the bulk of research articles
in biomedical fields. At the same time, the publication of databases of biological information …

Background and objective In order for computers to extract useful information from
unstructured text, a concept normalization system is needed to link relevant concepts in a …

Many machine learning methods have been applied on the biomedical named entity
recognition and achieve good results on GENIA corpus. However most of those methods …

Hubris is a known risk for leadership failure. We show that hubristic tendencies can be
detected semantically ex-ante in textual reports, and offer a novel methodology aimed at …

Text is a very important type of data within the biomedical domain. For example, patient
records contain large amounts of text which has been entered in a non-standardized format …

Background Many biomedical relation extraction systems are machine-learning based and
have to be trained on large annotated corpora that are expensive and cumbersome to …

Protein-Protein Interactions (PPIs) information extraction from biomedical literature helps
unveil the molecular mechanisms of biological processes. Machine learning methods have …

Relation extraction (RE) is a fundamental task for extracting gene–disease associations from
biomedical text. Many state-of-the-art tools have limited capacity, as they can extract gene …