ArticleBMC bioinformatics2011
Exploring subdomain variation in biomedical language.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Supervised Relation Extraction Between Suicide-Related Entities and Drugs: Development and Usability Study of an Annotated PubMed Corpus.Journal of medical Internet research · 2023Article
- RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion.NAR genomics and bioinformatics · 2021Article
- Cardioinformatics: the nexus of bioinformatics and precision cardiology.Briefings in bioinformatics · 2020Article
- Biomedical text mining for research rigor and integrity: tasks, challenges, directions.Briefings in bioinformatics · 2018Article
- Using text analysis to quantify the similarity and evolution of scientific disciplines.Royal Society open science · 2018Article
- Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles.BMC bioinformatics · 2017Article
- The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance.Applied clinical informatics · 2017Article
- TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations.JMIR public health and surveillance · 2017Article
- Sublanguage Corpus Analysis Toolkit: A tool for assessing the representativeness and sublanguage characteristics of corpora.LREC ... International Conference on Language Resources & Evaluation : [proceedings]. International Conference on Language Resources & Evaluation · 2014Article
- Semi-supervised learning of causal relations in biomedical scientific discourse.Biomedical engineering online · 2014Article
- Redundancy-aware topic modeling for patient record notes.PloS one · 2014Article
- FlexiTerm: a flexible term recognition method.Journal of biomedical semantics · 2013Article
- BioCause: Annotating and analysing causality in the biomedical domain.BMC bioinformatics · 2013Article
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Authors and funding
3 authors.
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Abstract
backgroundApplications of Natural Language Processing (NLP) technology to biomedical texts have generated significant interest in recent years. In this paper we identify and investigate the phenomenon of linguistic subdomain variation within the biomedical domain, i.e., the extent to which different subject areas of biomedicine are characterised by different linguistic behaviour. While variation at a coarser domain level such as between newswire and biomedical text is well-studied and known to affect the portability of NLP systems, we are the first to conduct an extensive investigation into more fine-grained levels of variation.
resultsUsing the large OpenPMC text corpus, which spans the many subdomains of biomedicine, we investigate variation across a number of lexical, syntactic, semantic and discourse-related dimensions. These dimensions are chosen for their relevance to the performance of NLP systems. We use clustering techniques to analyse commonalities and distinctions among the subdomains.
conclusionsWe find that while patterns of inter-subdomain variation differ somewhat from one feature set to another, robust clusters can be identified that correspond to intuitive distinctions such as that between clinical and laboratory subjects. In particular, subdomains relating to genetics and molecular biology, which are the most common sources of material for training and evaluating biomedical NLP tools, are not representative of all biomedical subdomains. We conclude that an awareness of subdomain variation is important when considering the practical use of language processing applications by biomedical researchers.
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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.