Broad-coverage biomedical relation extraction with SemRep
Background In the era of information overload, natural language processing (NLP)
techniques are increasingly needed to support advanced biomedical information …
techniques are increasingly needed to support advanced biomedical information …
BioRel: towards large-scale biomedical relation extraction
Background Although biomedical publications and literature are growing rapidly, there still
lacks structured knowledge that can be easily processed by computer programs. In order to …
lacks structured knowledge that can be easily processed by computer programs. In order to …
BioRED: a rich biomedical relation extraction dataset
Automated relation extraction (RE) from biomedical literature is critical for many downstream
text mining applications in both research and real-world settings. However, most existing …
text mining applications in both research and real-world settings. However, most existing …
Constructing a semantic predication gold standard from the biomedical literature
H Kilicoglu, G Rosemblat, M Fiszman, TC Rindflesch - BMC bioinformatics, 2011 - Springer
Background Semantic relations increasingly underpin biomedical text mining and
knowledge discovery applications. The success of such practical applications crucially …
knowledge discovery applications. The success of such practical applications crucially …
Biomedical relation extraction via knowledge-enhanced reading comprehension
Background In biomedical research, chemical and disease relation extraction from
unstructured biomedical literature is an essential task. Effective context understanding and …
unstructured biomedical literature is an essential task. Effective context understanding and …
A novel machine learning framework for automated biomedical relation extraction from large-scale literature repositories
Abstract Knowledge about the relations between biomedical entities (such as drugs and
targets) is widely distributed in more than 30 million research articles and consistently plays …
targets) is widely distributed in more than 30 million research articles and consistently plays …
[HTML][HTML] Multiple features for clinical relation extraction: A machine learning approach
I Alimova, E Tutubalina - Journal of biomedical informatics, 2020 - Elsevier
Relation extraction aims to discover relational facts about entity mentions from plain texts. In
this work, we focus on clinical relation extraction; namely, given a medical record with …
this work, we focus on clinical relation extraction; namely, given a medical record with …
Bridging semantics and syntax with graph algorithms—state-of-the-art of extracting biomedical relations
Research on extracting biomedical relations has received growing attention recently, with
numerous biological and clinical applications including those in pharmacogenomics, clinical …
numerous biological and clinical applications including those in pharmacogenomics, clinical …
Multichannel convolutional neural network for biological relation extraction
The plethora of biomedical relations which are embedded in medical logs (records)
demands researchers' attention. Previous theoretical and practical focuses were restricted …
demands researchers' attention. Previous theoretical and practical focuses were restricted …
A span-graph neural model for overlapping entity relation extraction in biomedical texts
Motivation Entity relation extraction is one of the fundamental tasks in biomedical text
mining, which is usually solved by the models from natural language processing. Compared …
mining, which is usually solved by the models from natural language processing. Compared …