Evidence map›Paper›PMID 27570676›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2016

Finding Related Publications: Extending the Set of Terms Used to Assess Article Similarity.

Wei Wei, Rebecca Marmor, Siddharth Singh, Shuang Wang, Dina Demner-Fushman, Tsung-Ting Kuo, Chun-Nan Hsu, Lucila Ohno-Machado

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

8 authors.

Wei WeiHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;
Rebecca MarmorHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;
Siddharth SinghHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;
Shuang WangHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;
Dina Demner-FushmanNational Library of Medicine, National Institutes of Health, Bethesda, MD.
Tsung-Ting KuoHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;
Chun-Nan HsuHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;
Lucila Ohno-MachadoHealth System Department of Biomedical Informatics, UC San Diego, San Diego, CA;

Funding

BioCADDIE: Biomedical and healthCAre Data Discovery and Indexing Engine centerU24AI117966 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OHNO-MACHADO, LUCILA · 2014 to 2016
$10.9M
San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
Protecting the pRivacy Of Genomes in REsearch StudieS (PROGRESS)R00HG008175 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WANG, SHUANG · 2016 to 2018
$527k
NHGRI NIH HHS R00 HG008175NIAID NIH HHS U24 AI117966NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

Recommendation of related articles is an important feature of the PubMed. The PubMed Related Citations (PRC) algorithm is the engine that enables this feature, and it leverages information on 22 million citations. We analyzed the performance of the PRC algorithm on 4584 annotated articles from the 2005 Text REtrieval Conference (TREC) Genomics Track data. Our analysis indicated that the PRC highest weighted term was not always consistent with the critical term that was most directly related to the topic of the article. We implemented term expansion and found that it was a promising and easy-to-implement approach to improve the performance of the PRC algorithm for the TREC 2005 Genomics data and for the TREC 2014 Clinical Decision Support Track data. For term expansion, we trained a Skip-gram model using the Word2Vec package. This extended PRC algorithm resulted in higher average precision for a large subset of articles. A combination of both algorithms may lead to improved performance in related article recommendations.

Identifiers

PMID27570676
PMCPMC5001748

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.