ArticleBMC bioinformatics2013
MeSH indexing based on automatically generated summaries.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Automated indexing in MEDLINE and the Medical Text Indexer (MTI), 2000-2025: a scoping review.Journal of the Medical Library Association : JMLA · 2026Article
- Benchmarking large language models for extracting biobank-derived insights into health and disease.PLoS computational biology · 2026Article
- Sometimes the apple does fall far from the tree: a case study on automatic indexing precision errors in PubMed.Journal of the Medical Library Association : JMLA · 2025Article
- Use of 'Pharmaceutical services' Medical Subject Headings (MeSH) in articles assessing pharmacists' interventions.Exploratory research in clinical and social pharmacy · 2022Article
- CERC: an interactive content extraction, recognition, and construction tool for clinical and biomedical text.BMC medical informatics and decision making · 2020Article
- FullMeSH: improving large-scale MeSH indexing with full text.Bioinformatics (Oxford, England) · 2020Article
- Perspective: An Extension of the STROBE Statement for Observational Studies in Nutritional Epidemiology (STROBE-nut): Explanation and Elaboration.Advances in nutrition (Bethesda, Md.) · 2017Article
- Boosting for high-dimensional two-class prediction.BMC bioinformatics · 2015Article
- MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence.Bioinformatics (Oxford, England) · 2015Article
- An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition.BMC bioinformatics · 2015Article
- Feasibility and implementation of a literature information management system for human papillomavirus in head and neck cancers with imaging.Cancer informatics · 2014Article
- Stochastic Gradient Descent and the Prediction of MeSH for PubMed Records.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.Database : the journal of biological databases and curation · 2013Article
- Extracting Characteristics of the Study Subjects from Full-Text Articles.AMIA ... Annual Symposium proceedings. AMIA SymposiumArticle
- Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundMEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results.
resultsWe have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision.
conclusionsOur results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading.
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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.