ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2013
Comparison and combination of several MeSH indexing approaches.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Trends in use of the new MeSH term "overdiagnosis": A bibliometric review.Health information and libraries journal · 2025Pooled it
- Automated indexing in MEDLINE and the Medical Text Indexer (MTI), 2000-2025: a scoping review.Journal of the Medical Library Association : JMLA · 2026Article
- Chemical identification and indexing in PubMed full-text articles using deep learning and heuristics.Database : the journal of biological databases and curation · 2022Article
- pyMeSHSim: an integrative python package for biomedical named entity recognition, normalization, and comparison of MeSH terms.BMC bioinformatics · 2020Article
- A probabilistic automated tagger to identify human-related publications.Database : the journal of biological databases and curation · 2018Article
- Article
- MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank.Journal of biomedical semantics · 2017Article
- DeepMeSH: deep semantic representation for improving large-scale MeSH indexing.Bioinformatics (Oxford, England) · 2016Article
- Convolutional Neural Networks for Biomedical Text Classification: Application in Indexing Biomedical Articles.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2015Article
- MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence.Bioinformatics (Oxford, England) · 2015Article
- Feature engineering for MEDLINE citation categorization with MeSH.BMC bioinformatics · 2015Article
- Overview of the gene ontology task at BioCreative IV.Database : the journal of biological databases and curation · 2014Article
- Stochastic Gradient Descent and the Prediction of MeSH for PubMed Records.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
MeSH indexing of MEDLINE is becoming a more difficult task for the group of highly qualified indexing staff at the US National Library of Medicine, due to the large yearly growth of MEDLINE and the increasing size of MeSH. Since 2002, this task has been assisted by the Medical Text Indexer or MTI program. We extend previous machine learning analysis by adding a more diverse set of MeSH headings targeting examples where MTI has been shown to perform poorly. Machine learning algorithms exceed MTI's performance on MeSH headings that are used very frequently and headings for which the indexing frequency is very low. We find that when we combine the MTI suggestions and the prediction of the learning algorithms, the performance improves compared to any single method for most of the evaluated MeSH headings.
Indexed as
Identifiers
24551371PMC3900212What 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.