ReviewComputational and mathematical methods in medicine2014
Biomedical relation extraction: from binary to complex.
Review in Computational and mathematical methods in medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
25 citing papers in PubMed, 93 citations in OpenAlex.
- The Role of N-ary Relations in Representing Biomedical Complexity.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Knowledge-augmented pre-trained language models for biomedical relation extraction.BMC bioinformatics · 2025Article
- Knowledge graph for traditional Chinese medicine diagnosis and treatment of diabetic retinopathy: design, construction, and applications.International journal of ophthalmology · 2025Article
- Conceptual design of a decision knowledge service model integrating a multi-agent supply relationship diagram for electric power emergency equipment.Frontiers in big data · 2025Article
- Biomedical relation extraction method based on ensemble learning and attention mechanism.BMC bioinformatics · 2024Article
- A framework for integrating biomedical knowledge in Wikidata with open biological and biomedical ontologies and MeSH keywords.Heliyon · 2024Article
- Exploring COVID-related relationship extraction: Contrasting data sources and analyzing misinformation.Heliyon · 2024Article
- A Study of Biomedical Relation Extraction Using GPT Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Large language model based framework for automated extraction of genetic interactions from unstructured data.PloS one · 2024Article
- BioEGRE: a linguistic topology enhanced method for biomedical relation extraction based on BioELECTRA and graph pointer neural network.BMC bioinformatics · 2023Article
- Article
- Constructing a disease database and using natural language processing to capture and standardize free text clinical information.Scientific reports · 2023Article
- Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach.BMC medical informatics and decision making · 2023Article
- Chemical-protein relation extraction with ensembles of carefully tuned pretrained language models.Database : the journal of biological databases and curation · 2022Article
- BertSRC: transformer-based semantic relation classification.BMC medical informatics and decision making · 2022Article
- On Building and Evaluating a Medical Records Exploration Interface Using Text Mining Techniques.Entropy (Basel, Switzerland) · 2021Article
- Mining microbe-disease interactions from literature via a transfer learning model.BMC bioinformatics · 2021Article
- Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network.Scientific reports · 2021Article
- Chemical-induced disease extraction via recurrent piecewise convolutional neural networks.BMC medical informatics and decision making · 2018Article
- Dependency-based long short term memory network for drug-drug interaction extraction.BMC bioinformatics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.