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

TL;DR

BERN2 is an advanced neural network-based tool that significantly improves the speed and accuracy of biomedical named entity recognition and normalization, aiding large-scale biomedical text annotation.

Contribution

It introduces a multi-task NER model and neural network-based NEN models, enhancing performance over previous tools in biomedical text processing.

Findings

Faster inference compared to previous tools

Higher accuracy in entity recognition and normalization

Facilitates large-scale biomedical text annotation

Abstract

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.