Mining MEDLINE for problems associated with vitamin D.

Dina Demner-Fushman, James G Mork, Alan R Aronson

Abstract readEvaluation Study

In one paragraph

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. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dina Demner-FushmanLister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, National Institutes of Health, DHHS, Bethesda, MD.

James G MorkLister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, National Institutes of Health, DHHS, Bethesda, MD.

Alan R AronsonLister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, National Institutes of Health, DHHS, Bethesda, MD.

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025

$5200.7M

Intramural NIH HHS

6 · The paper itself

Abstract

This paper presents a two-step approach to generating comprehensive abstractive overviews for biomedical topics. It starts with a sensitivity-maximizing search of MEDLINE/PubMed and MeSH-based filtering of the results that are then processed using NLP methods to extract relations between entities of interest. We evaluate this approach in a case study based on the IOM report on the role of vitamin D in human health. The report defines disorders that serve as health indicators for the role of vitamin D. We evaluate the abstractive overviews generated using MeSH indexing and the extracted relations using the disorders listed in the IOM report as reference standard. We conclude that MeSH-based aggregation and filtering of the results is a useful and easy step in the generation of abstractive overviews. Although our relation extraction achieved 83.6% recall and 92.8% precision, only half of the disorders of interest participated in these relations.

Indexed as

Abstracting and IndexingData MiningMedical Subject HeadingsMEDLINENatural Language ProcessingVitamin DCalciumDietary SupplementsHumansVitamin D DeficiencyCalciumVitamin D

Identifiers

PMID24551339

PMCPMC3900180

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

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.