ArticleJournal of biomedical semantics2017
MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank.
Article in Journal of biomedical semantics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A multiyear systematic survey of the quality of reporting for randomised trials in dentistry, neurology and geriatrics published in journals of Spain and Latin America.BMC medical research methodology · 2021Pooled it
- [Scientific output of the Revista Médica del IMSS in PubMed (2005-2025): a bibliometric analysis].Revista medica del Instituto Mexicano del Seguro Social · 2026Article
- Annotating and indexing scientific articles with rare diseases.Journal of biomedical semantics · 2026Article
- The Perspective on Secondary Research Practices: A Cross-Sectional Analysis.Healthcare (Basel, Switzerland) · 2025Article
- Algorithmic indexing in MEDLINE frequently overlooks important concepts and may compromise literature search results.Journal of the Medical Library Association : JMLA · 2025Article
- Automatic Classification and Visualization of Text Data on Rare Diseases.Journal of personalized medicine · 2024Article
- What's next? Forecasting scientific research trends.Heliyon · 2024Article
- NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data.Frontiers in neuroinformatics · 2023Article
- Chemical identification and indexing in PubMed full-text articles using deep learning and heuristics.Database : the journal of biological databases and curation · 2022Article
- Multi-probe attention neural network for COVID-19 semantic indexing.BMC bioinformatics · 2022Article
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- Thesaurus-based word embeddings for automated biomedical literature classification.Neural computing & applications · 2022Article
- How to catch trends using MeSH terms analysis?Scientometrics · 2022Article
- Recent advances in biomedical literature mining.Briefings in bioinformatics · 2021Review
- Biomedical articles share annotations with their citation neighbors.BMC bioinformatics · 2021Article
- Tackling Research Inefficiency in Degenerative Cervical Myelopathy: Illustrative Review.JMIR research protocols · 2020Article
- FullMeSH: improving large-scale MeSH indexing with full text.Bioinformatics (Oxford, England) · 2020Article
- A Review of Cancer Genetics and Genomics Studies in Africa.Frontiers in oncology · 2020Review
- ML-Net: multi-label classification of biomedical texts with deep neural networks.Journal of the American Medical Informatics Association : JAMIA · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundMeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized.
methodsWe propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module.
resultsWe assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F
conclusionsWe conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. AVAILABILITY: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ .
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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.