Evidence map›Paper›PMID 33066086›Full record

ArticleInternational journal of environmental research and public health2020

Tracking Knowledge Evolution Based on the Terminology Dynamics in 4P-Medicine.

Aida Khakimova, Xuejie Yang, Oleg Zolotarev, Maria Berberova, Michael Charnine

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Aida KhakimovaAutonomous Nonprofit Organization, Research Center for Physical and Technical Informatics, Nizhny Novgorod 603098, Russia.ORCID 0000-0001-9355-9249
Xuejie YangSchool of Management, Hefei University of Technology, Hefei 230009, China.
Oleg ZolotarevAutonomous Nonprofit Organization of Higher Education, Russian New University, Moscow 105005, Russia.ORCID 0000-0001-6917-9668
Maria BerberovaAutonomous Nonprofit Organization of Higher Education, Russian New University, Moscow 105005, Russia.
Michael CharnineInstitute of Informatics Problems of the FRC CSC, the Russian Academy of Sciences, Moscow 119333, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accelerating evolution of scientific terms connected with 4P-medicine terminology and a need to track this process has led to the development of new methods of analysis and visualization of unstructured information. We built a collection of terms especially extracted from the PubMed database. Statistical analysis showed the temporal dynamics of the formation of derivatives and significant collocations of medical terms. We proposed special linguistic constructs such as megatokens for combining cross-lingual terms into a common semantic field. To build a cyberspace of terms, we used modern visualization technologies. The proposed approaches can help solve the problem of structuring multilingual heterogeneous information. The purpose of the article is to identify trends in the development of terminology in 4P-medicine.

Indexed as

MedicineSemanticsTerminology as TopicDatabases, FactualHumansLinguisticsVirtual Reality4P-medicinecyberspaceinformative terminterlanguage semantic similaritymegalemmamegatokenvirtual realityWebVR

Identifiers

PMID33066086
PMCPMC7600767

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.