Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host
interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to …

Named-entity recognition (NER) aims at identifying entities of interest in a text. Artificial
neural networks (ANNs) have recently been shown to outperform existing NER systems …

Background Finding biomedical named entities is one of the most essential tasks in
biomedical text mining. Recently, deep learning-based approaches have been applied to …

Named entity recognition (NER) is a fundamental task in Chinese natural language
processing (NLP) tasks. Recently, Chinese clinical NER has also attracted continuous …

Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop.
In this task participants designed systems to identify substrings in sentences corresponding …

With the rapid advancement of technology and the necessity of processing large amounts of
data, biomedical Named Entity Recognition (NER) has become an essential technique for …

There has been an increasing amount of research on biomedical named entity recognition,
the most basic text extraction problem, resulting in significant progress by different research …

Motivation Best performing named entity recognition (NER) methods for biomedical literature
are based on hand-crafted features or task-specific rules, which are costly to produce and …

Thanks to the increasing availability of genomics and other biomedical data, many machine
learning algorithms have been proposed for a wide range of therapeutic discovery and …

Background Biomedical named entity recognition (BNER) is a crucial initial step of
information extraction in biomedical domain. The task is typically modeled as a sequence …