Sociology

Biomedical text mining

Inference

Knowledge base

Normalization (sociology)

Machine learning

Artificial intelligence

Management

Economics

Anthropology

Natural language processing

Information retrieval

Named entity

Named-entity recognition

Computer science

Task (project management)

Artificial neural network

Text mining

Entity linking

Bioinformatics

In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature. In this article, we present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by employing a multi-task NER model and neural network-based NEN models to achieve much faster and more accurate inference. We hope that our tool can help annotate large-scale biomedical texts for various tasks such as biomedical knowledge graph construction.Web service of BERN2 is publicly available at http://bern2.korea.ac.kr. We also provide local installation of BERN2 at https://github.com/dmis-lab/BERN2.Supplementary data are available at Bioinformatics online.

BERN2: an advanced neural biomedical named entity recognition and normalization tool