scholarly journals Constructing Japanese MeSH term dictionaries related to the COVID-19 literature

2021 ◽  
Vol 19 (3) ◽  
pp. e25
Author(s):  
Atsuko Yamaguchi ◽  
Terue Takatsuki ◽  
Yuka Tateisi ◽  
Felipe Soares
Keyword(s):  
Mesh Term ◽  
Research Papers ◽  
Medical Terms ◽  
Japanese Speakers ◽  
Mesh Terms

The coronavirus disease 2019 (COVID-19) pandemic has led to a flood of research papers and the information has been updated with considerable frequency. For society to derive benefits from this research, it is necessary to promote sharing up-to-date knowledge from these papers. However, because most research papers are written in English, it is difficult for people who are not familiar with English medical terms to obtain knowledge from them. To facilitate sharing knowledge from COVID-19 papers written in English for Japanese speakers, we tried to construct a dictionary with an open license by assigning Japanese terms to MeSH unique identifiers (UIDs) annotated to words in the texts of COVID-19 papers. Using this dictionary, 98.99% of all occurrences of MeSH terms in COVID-19 papers were covered. We also created a curated version of the dictionary and uploaded it to PubDictionary for wider use in the PubAnnotation system.

The Most Cited Mesh Terms and Authors who Published Papers in Pubmed Central on the Topic of Medicine and Health Using Bibliometric Analyses

2019 ◽  
pp. 1-9
Author(s):  
Tsair-Wei Chien ◽  
Hing-Man Wu ◽  
Hsien-Yi Wang ◽  
Willy Chou
Keyword(s):  
Mesh Term ◽  
Deep Insight ◽  
Medical Subject Headings ◽  
Microsoft Excel ◽  
Pubmed Central ◽  
Current State ◽  
Mesh Terms ◽  
Control Gain ◽  
State Of Research ◽  
Insight Into

Aims: We visualized the current state of research on publication outputs and citations in the field of medicine and health to uncover topic burst and citations among medical subject headings (MeSH) clusters. Study Design: A bibliometric analysis. Place and duration of Study: Using Pubmed indexed articles to inspect the characteristics of topics on medicine and health since 1969. Methodology: Selecting 156 abstracts, author names, countries, and MeSH terms on January 10, 2019, from Pubmed Central (PMC) based on the terms of medicine and health in the title since 1969, we applied the x-index and impact factor to evaluate author individual research achievements and compute MeSH bibliometric performances. The bootstrapping method was used to estimate the median and its 95% confidence intervals and make differences in metrics among MeSH clusters. The dominant nations were selected using the x-index to display on a dashboard. We programmed Microsoft Excel VBA routines to extract data. Google Maps and Pajek software were used for displaying graphical representations. Results: We found that (1)the dominant countries/areas are the Unlited States, Taiwan, and Australia; (2) the author Grajales, Francisco Jose 3rd form Canada has the most cited metrics such as author IF=39.46 and x-index=6.28; (3)the MeSH terms of organization & administration, standards, and prevention & control gain the top three degree centralities among MeSH clusters; (4) No any differences in metrics were found among MeSH clusters; (5) the article(PMID= 24518354) with three MeSH term of delivery of health care, social media, and software and published in 2014 was cited most at least 62 times. Conclusion: Social network analysis provides wide and deep insight into the relationships among MeSH terms. The MeSH weighted scheme and x-index were recommended to academics for computing MeSH citations in the future.

scholarly journals MeSHDD: Literature-based drug-drug similarity for drug repositioning

2016 ◽  
Vol 24 (3) ◽  
pp. 614-618 ◽  
Author(s):  
Adam S Brown ◽  
Chirag J Patel
Keyword(s):  
Drug Repositioning ◽  
Mesh Term ◽  
Medical Subject Heading ◽  
Mesh Terms ◽  
Interactive Application ◽  
Diabetes Drug ◽  
The Cost ◽  
Novel Drug ◽  
Drug Similarity ◽  
Discovery Pipeline

Objective: Drug repositioning is a promising methodology for reducing the cost and duration of the drug discovery pipeline. We sought to develop a computational repositioning method leveraging annotations in the literature, such as Medical Subject Heading (MeSH) terms. Methods: We developed software to determine significantly co-occurring drug-MeSH term pairs and a method to estimate pair-wise literature-derived distances between drugs. Results We found that literature-based drug-drug similarities predicted the number of shared indications across drug-drug pairs. Clustering drugs based on their similarity revealed both known and novel drug indications. We demonstrate the utility of our approach by generating repositioning hypotheses for the commonly used diabetes drug metformin. Conclusion: Our study demonstrates that literature-derived similarity is useful for identifying potential repositioning opportunities. We provided open-source code and deployed a free-to-use, interactive application to explore our database of similarity-based drug clusters (available at http://apps.chiragjpgroup.org/MeSHDD/).

scholarly journals Theme trends in research related to retinal vein occlusion: a quantitative and co-word analysis

2019 ◽  
Author(s):  
Fei Liu ◽  
Ximei Chen ◽  
Miao Zhao
Keyword(s):  
Retinal Vein Occlusion ◽  
Research Output ◽  
Knowledge Structure ◽  
Mesh Term ◽  
Diagnostic Methods ◽  
Vein Occlusion ◽  
Mesh Terms ◽  
Occurrence Matrix ◽  
Surgical Treatments ◽  
Node Position

Abstract Background. This study focused on plotting knowledge structure and exploring research hotspots of retinal vein occlusion (RVO). Methods. In this study, research articles, with subject of RVO, were acquired from PubMed. Bibliographic Item Co-Occurrence Matrix Builder (BICOMB) was used for MeSH terms acquisition, evaluation and high-frequency MeSH term determination. Biclustering analysis and knowledge structure were conducted based on the MeSH term-source article matrix. RVO theme trends were illustrated with social network analysis (SNA), along with strategic diagrams. Results. A total of 3179 articles on RVO were retrieved, and the annual research output increased with time. USA ranked first with the most publications, with Retina as the most prolific journal in RVO research. MeSH terms were characterized into five different genres. As shown by the strategic diagram, the complications of RVO, the etiology of macular edema, as well as the therapeutic use of anti-VEGF, steroids and anti-inflammatory agents were well developed (Quadrant I). In contrast, epidemiology, metabolism and genetics related research on RVO were relatively immature (Quadrant III). Research on surgical treatments of vitrectomy, diagnostic methods and pathology of RVO were centralized but undeveloped (Quadrant IV). The SNA results was exhibited by the centrality chart, on which the node position was represented by the centrality values. Conclusions. By providing a bibliometric research, the overall RVO research trends could be revealed based on the five categories identified by this study. The mathematical bibliometric study could shed light on new perspectives for researchers.

scholarly journals ETHYMOLOGY OF MEDICAL TERMS TRANSLATED INTO UZBEK FROM OTHER LANGUAGES

2021 ◽  
pp. 315-321
Author(s):  
Suyunov Bakhodir
Keyword(s):  
Modern Medicine ◽  
Semantic Features ◽  
Research Papers ◽  
Word Acquisition ◽  
Medical Terms ◽  
Scientific Hypothesis ◽  
Component Content ◽  
The Subject ◽  
Cultural Linguistics ◽  
Cultural Features

This article of the author is devoted to the etymology of medical terms that have been introduced into the Uzbek language from other languages. It also discusses the vocabulary, socio-historical development of the Uzbek language, its relationship with other languages and the peculiarities of word acquisition. The article analyzes medical terms, mainly from Arabic to Uzbek. In the process of analysis, the origin and semantic features of these lexical units have been thoroughly studied theoretically and practically. In this regard, the author effectively used scientific sources in Uzbek and Russian languages, as well as various dictionaries and research papers, and expressed his scientific hypothesis. Instead, he drew relevant scientific conclusions on the subject by referring to examples and evidence that differentiate the same concepts and phenomena. In particular, the article describes the etymology and national-cultural features of medical terms borrowed from Arabic into Uzbek - linguoculturology on the basis of historical and synchronous, comparative and component analysis methods. For example, the use of the complication lexeme in the Uzbek language in the sense of a sign, trace, specific feature, which appeared or appeared after an event, is associated with modern medicine in the example of today’s infectious, acute respiratory disease pandemic covid-2019. Attention is also paid to the synonym of the complication lexeme in the Uzbek language and its homonym. Many such original examples can be cited from the article. So, all of the above in a sense determines the scientific-theoretical and practical value of this article. KEYWORDS: etymology, semantics, grammar, structure, cell, masdar, sukun, uzv, cultural linguistics, component, content, lexeme, term, phraseme, neologism, respirator, pandemic, anomaly.

Symptoms of Adenomyosis and Overlapping Diseases

2020 ◽  
Vol 38 (02/03) ◽  
pp. 144-150 ◽  
Author(s):  
Keith Isaacson ◽  
Megan Loring
Keyword(s):  
Age Of Onset ◽  
Current Knowledge ◽  
Transvaginal Ultrasound ◽  
Mesh Term ◽  
Noninvasive Diagnostics ◽  
Younger Women ◽  
Mesh Terms ◽  
Text Word ◽  
Magnetic Resonance Imaging Mri ◽  
Pain Symptoms

AbstractTo summarize and update our current knowledge regarding adenomyosis diagnosis, prevalence, and symptoms. Systematic review of PubMed between January 1972 and April 2020. Search strategy included: “adenomyosis [MeSH Terms] AND (endometriosis[MeSH Term OR prevalence study [MeSH Terms] OR dysmenorrhea[Text Word] OR prevalence[Text Word] OR young adults [Text Word] OR adolesce* [Text Word] OR symptoms[Text Word] OR imaging diagnosis [Text Word] OR pathology[Text Word]. Articles published in English that addressed adenomyosis and discussed prevalence, diagnosis, and symptoms were included. Included articles described: pathology diagnosis, imaging, biopsy diagnosis, prevalence and age of onset, symptoms, and concomitant endometriosis. Sixteen articles were included in the qualitative analysis. The studies are heterogeneous when diagnosing adenomyosis with differing criteria, protocols, and patient populations. Prevalence estimates range from 20% to 88.8% in symptomatic women (average 30–35%) with most diagnosed between 32–38 years old. The correlation between imaging and pathology continues to evolve. As imaging advances, newer studies report younger symptomatic women are being diagnosed with adenomyosis based on both magnetic resonance imaging (MRI) and/or transvaginal ultrasound (TVUS). High rates of concomitant endometriosis create challenges when discerning the etiology of pelvic pain. Symptoms that are historically attributed to endometriosis may actually be caused by adenomyosis. Adenomyosis remains a challenge to identify, assess and research because of the lack of standardized diagnostic criteria, especially in women who wish to retain their uterus. As noninvasive diagnostics such as imaging and myometrial biopsies continue to improve, younger women with variable symptoms will likely create criteria for diagnosis with adenomyosis. The priority should be to create standardized histopathological and imaging diagnoses to gain deeper understandings of adenomyosis.

scholarly journals Human Breathomics Database

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Tien-Chueh Kuo ◽  
Cheng-En Tan ◽  
San-Yuan Wang ◽  
Olivia A Lin ◽  
Bo-Han Su ◽  
...  
Keyword(s):  
Text Mining ◽  
Exhaled Breath Condensate ◽  
Mesh Term ◽  
Exhaled Breath ◽  
Medical Subject Headings ◽  
Mesh Terms ◽  
Disease Information ◽  
Volatile Organic ◽  
Breath Condensate ◽  
Automatic Pipeline

Abstract Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database—the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw

Retrieval and Classification of Dental Research Articles

2003 ◽  
Vol 17 (1) ◽  
pp. 115-120 ◽  
Author(s):  
W.C. Bartling ◽  
T.K. Schleyer ◽  
S. Visweswaran
Keyword(s):  
Mesh Term ◽  
Research Literature ◽  
Research Articles ◽  
Test Set ◽  
Dental Research ◽  
Text Input ◽  
Mesh Terms ◽  
Successful Retrieval ◽  
Better Than

Successful retrieval of a corpus of literature on a broad topic can be difficult. This study demonstrates a method to retrieve the dental and craniofacial research literature. We explored MeSH manually for dental or craniofacial indexing terms. MEDLINE was searched using these terms, and a random sample of references was extracted from the resulting set. Sixteen dental research experts categorized these articles, reading only the title and abstract, as either: (1) dental research, (2) dental non-research, (3) non-dental, or (4) not sure. Identify Patient Sets (IPS), a probabilistic text classifier, created models, based on the presence or absence of words or UMLS phrases, that distinguished dental research articles from all others. These models were applied to a test set with different inputs for each article: (1) title and abstract only, (2) MeSH terms only, or (3) both. By title and abstract only, IPS correctly classified 64% of all dental research articles present in the test set. The percentage of correctly classified dental research articles in this retrieved set was 71%. MeSH term inclusion decreased performance. Computer programs that use text input to categorize articles may aid in retrieval of a broad corpus of literature better than indexing terms or key words alone.

scholarly journals BioLitMine: Advanced Mining of Biomedical and Biological Literature About Human Genes and Genes from Major Model Organisms

2020 ◽  
Vol 10 (12) ◽  
pp. 4531-4539
Author(s):  
Yanhui Hu ◽  
Verena Chung ◽  
Aram Comjean ◽  
Jonathan Rodiger ◽  
Fnu Nipun ◽  
...  
Keyword(s):  
Relevant Literature ◽  
Gene List ◽  
Citation Network ◽  
Relevant Information ◽  
Mesh Term ◽  
Biomedical Literature ◽  
Model Organisms ◽  
Literature Mining ◽  
Mesh Terms ◽  
Human Genes

The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH term, such as a list of genes relevant to “stem cells” or “breast neoplasms.” Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.

scholarly journals Using MeSH (Medical Subject Headings) to Enhance PubMed Search Strategies for Evidence-Based Practice in Physical Therapy

2012 ◽  
Vol 92 (1) ◽  
pp. 124-132 ◽  
Author(s):  
Randy R. Richter ◽  
Tricia M. Austin
Keyword(s):  
Search Strategy ◽  
Evidence Based Practice ◽  
Physical Therapists ◽  
Mesh Term ◽  
Evidence Based ◽  
Medical Subject Headings ◽  
Search Terms ◽  
Mesh Terms ◽  
Subject Headings ◽  
Pubmed Search

Background Evidence-based practice (EBP) is an important paradigm in health care. Physical therapists report lack of knowledge and time constraints as barriers to EBP. Objective The purpose of this technical report is to illustrate how Medical Subject Headings (MeSH), a controlled vocabulary thesaurus of indexing terms, is used to efficiently search MEDLINE, the largest component of PubMed. Using clinical questions, this report illustrates how search terms common to physical therapist practice do or do not map to appropriate MeSH terms. A PubMed search strategy that takes advantage of text words and MeSH terms is provided. Results A search of 139 terms and 13 acronyms was conducted to determine whether they appropriately mapped to a MeSH term. The search results were categorized into 1 of 5 outcomes. Nearly half (66/139) of the search terms mapped to an appropriate MeSH term (outcome 1). When a search term did not appropriately map to a MeSH term, it was entered into the MeSH database to search for an appropriate MeSH term. Twenty-one appropriate MeSH terms were found (outcomes 2 and 4), and there were 52 search terms for which an appropriate MeSH term was not found (outcomes 3 and 5). Nearly half of the acronyms did not map to an appropriate MeSH term, and an appropriate MeSH term was not found in the database. Limitations The results are based on a limited number of search terms and acronyms. Conclusions Understanding how search terms map to MeSH terms and using the PubMed search strategy can enable physical therapists to take full advantage of available MeSH terms and should result in more-efficient and better-informed searches.

The Role of Technology and Informatics in Disaster Planning and Response

2012 ◽  
Vol 30 (1) ◽  
pp. 149-168 ◽  
Author(s):  
Elizabeth Weiner ◽  
Lynn A. Slepski
Keyword(s):  
Disaster Planning ◽  
Mesh Term ◽  
Disaster Medicine ◽  
Medical Subject Headings ◽  
Humanitarian Response ◽  
Mesh Terms ◽  
Pubmed Search ◽  
Impact Of Technology ◽  
The Impact

It is clear that technology and informatics are becoming increasingly important in disasters and humanitarian response. Technology is a critical tool to recording, analyzing, and predicting trends in data that could not be achieved prior to its implementation. Informatics is the translation of this data into information, knowledge, and wisdom. Combining technology and informatics applications with response efforts has resulted in various enhanced biosurveillance efforts, advanced communications, and information management during disasters. Although these efforts have been well described in the literature, research on the impact of technology and informatics during these efforts has been limited. As a result, this chapter will provide an overview of these technology and informatics solutions and present suggestions for further research in an era when disaster and humanitarian response efforts continue to increase as well. A literature search was performed using PubMed search tools with the National Library of Medicine Medical Subject Headings (MeSH) terms of “disasters,” “disaster planning,” “disaster medicine,” “technology,” “informatics,” and “research.” Search limitations were set for 5 years and in English. Because of the limited number of research articles in this field, the MeSH term research was deleted.

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