ArticleNeuroinformatics2003
Text mining neuroscience journal articles to populate neuroscience databases.
Article in Neuroinformatics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.Acta neurochirurgica. Supplement · 2022Pooled it
- An analysis of the abstracts presented at the annual meetings of the Society for Neuroscience from 2001 to 2006.PloS one · 2008Pooled it
- A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience.Neuroinformatics · 2019Article
- Automated Metadata Suggestion During Repository Submission.Neuroinformatics · 2019Article
- Using text mining to link journal articles to neuroanatomical databases.The Journal of comparative neurology · 2012Article
- Automated recognition of brain region mentions in neuroscience literature.Frontiers in neuroinformatics · 2009Article
- PepBank--a database of peptides based on sequence text mining and public peptide data sources.BMC bioinformatics · 2007Article
- SenseLab: new developments in disseminating neuroscience information.Briefings in bioinformatics · 2007Article
- A hybrid approach to shape-based interpolation of stereotactic atlases of the human brain.Neuroinformatics · 2006Article
- Semi-automated population of an online database of neuronal models (ModelDB) with citation information, using PubMed for validation.Neuroinformatics · 2004Article
- Creating knowledgebases to text-mine PUBMED articles using clustering techniques.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2003Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
We have developed a program NeuroText to populate the neuroscience databases in SenseLab (http://senselab.med.yale.edu/senselab) by mining the natural language text of neuroscience articles. NeuroText uses a two-step approach to identify relevant articles. The first step (pre-processing), aimed at 100% sensitivity, identifies abstracts containing database keywords. In the second step, potentially relevant abstracts identified in the first step are processed for specificity dictated by database architecture, and neuroscience, lexical and semantic contexts. NeuroText results were presented to the experts for validation using a dynamically generated interface that also allows expert-validated articles to be automatically deposited into the databases. Of the test set of 912 articles, 735 were rejected at the pre-processing step. For the remaining articles, the accuracy of predicting database-relevant articles was 85%. Twenty-two articles were erroneously identified. NeuroText deferred decisions on 29 articles to the expert. A comparison of NeuroText results versus the experts' analyses revealed that the program failed to correctly identify articles' relevance due to concepts that did not yet exist in the knowledgebase or due to vaguely presented information in the abstracts. NeuroText uses two "evolution" techniques (supervised and unsupervised) that play an important role in the continual improvement of the retrieval results. Software that uses the NeuroText approach can facilitate the creation of curated, special-interest, bibliography databases.
Indexed as
Identifiers
15046245What 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.