AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning.

ABSTRACT:

Motivation

Biomedical named entity recognition (BioNER) seeks to automatically recognize biomedical entities in natural language text, serving as a necessary foundation for downstream text mining tasks and applications such as information extraction and question answering. Manually labeling training data for the BioNER task is costly, however, due to the significant domain expertise required for accurate annotation. The resulting data scarcity causes current BioNER approaches to be prone to overfitting, to suffer from limited generalizability, and to address a single entity type at a time (e.g. gene or disease).

Results

We therefore propose a novel all-in-one (AIO) scheme that uses external data from existing annotated resources to enhance the accuracy and stability of BioNE

SUBMITTER: Luo L 

PROVIDER: S-EPMC10212279 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature