Abstract With Artificial Intelligence (AI) increasingly permeating various aspects of society,
including healthcare, the adoption of the Transformers neural network architecture is rapidly …

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

In this study, we investigate the problem of named entity recognition for tweets. Named entity
recognition is an important task in natural language processing and has been carefully …

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 …

We propose a sequence labeling framework with a secondary training objective, learning to
predict surrounding words for every word in the dataset. This language modeling objective …

Sequence labeling architectures use word embeddings for capturing similarity, but suffer
when handling previously unseen or rare words. We investigate character-level extensions …

Biomedical named entity recognition (BNER), which extracts important named entities such
as genes and proteins, is a challenging task in automated systems that mine knowledge in …

Named entity recognition is a crucial component of biomedical natural language processing,
enabling information extraction and ultimately reasoning over and knowledge discovery …

We describe here the JNLPBA shared task of bio-entity recognition using an extended
version of the GENIA version 3 named entity corpus of MEDLINE abstracts. We provide …

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 …