ArticleDatabase : the journal of biological databases and curation2014
Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus.
Article in Database : the journal of biological databases and curation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- PMC text mining subset in BioC: about three million full-text articles and growing.Bioinformatics (Oxford, England) · 2019Article
- iTextMine: integrated text-mining system for large-scale knowledge extraction from the literature.Database : the journal of biological databases and curation · 2018Article
- BioC viewer: a web-based tool for displaying and merging annotations in BioC.Database : the journal of biological databases and curation · 2016Article
- PubMedPortable: A Framework for Supporting the Development of Text Mining Applications.PloS one · 2016Article
- BioC interoperability track overview.Database : the journal of biological databases and curation · 2014Review
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net.
Indexed as
Identifiers
What OpenQuestion holds
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.