BioREx: Improving Biomedical Relation Extraction by Leveraging Heterogeneous Datasets.

ABSTRACT: Biomedical relation extraction (RE) is the task of automatically identifying and characterizing relations between biomedical concepts from free text. RE is a central task in biomedical natural language processing (NLP) research and plays a critical role in many downstream applications, such as literature-based discovery and knowledge graph construction. State-of-the-art methods were used primarily to train machine learning models on individual RE datasets, such as protein-protein interaction and chemical-induced disease relation. Manual dataset annotation, however, is highly expensive and time-consuming, as it requires domain knowledge. Existing RE datasets are usually domain-specific or small, which limits the development of generalized and high-performing RE models. In this work, we pres

SUBMITTER: Lai PT 

PROVIDER: S-EPMC10370213 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature