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 Four Facets to Know a Cancer Care-related Journal: An Example of Eur. J. Cancer Care (Engl.)

2020 ◽  
pp. 1-9
Author(s):  
Wan-Ting Hsieh ◽  
Tsair-Wei Chien ◽  
Willy Chou
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Rasch Model ◽  
Cancer Care ◽  
Deep Insight ◽  
Microsoft Excel ◽  
Pubmed Central ◽  
Productive Author ◽  
Insight Into ◽  
Productive Authors

Objective: This study aimed to investigate the journal features by collecting some data from Pubmed Central (PMC) and to interpret the characteristics of the journal for Eur J Cancer Care (Engl) (EJCC). Methods: Selecting 1611 abstracts and their corresponding author names and keywords on September 3, 2017, from PMC, we analyzed data mentioned above to address following features: (1) Nation distribution and author collaborations; (2) Journal features represented by article keywords; (3) The most productive authors and their authorship clusters; (4) The top 10 journals most similar to EJCC. Microsoft Excel VBA routines were programmed to extract data from PMC. Rasch model and SNA Pajek software were used to present visualized displays for EJCC features. Results: We found (1) the majority of the articles are from UK (28%) Australia (10%) and Sweden (5%); (2) The most linked Keywords are cancer and breast cancer; (3) The most productive author is R Sanson-Fisher; (4) The top one journal with the most similarity to EJCC is Support Care Cancer. Conclusion: Social network analysis that provides wide and deep insight into the relationships among nations, coauthor collaborations, abstract keywords and journals most similar to EJCC was performed in this study. The results can be provided to strategy and decision making for the target journal in the future.

scholarly journals Salivary protein roles in oral health and as predictors of caries risk

2018 ◽  
Vol 13 (1) ◽  
pp. 174-200
Author(s):  
Galina Laputková ◽  
Vladimíra Schwartzová ◽  
Juraj Bánovčin ◽  
Michal Alexovič ◽  
Ján Sabo
Keyword(s):  
Dental Caries ◽  
Oral Cavity ◽  
Human Saliva ◽  
Salivary Protein ◽  
Oral Diseases ◽  
Irreversible Damage ◽  
Current State ◽  
Whole Saliva ◽  
State Of Research ◽  
Insight Into

AbstractThis work describes the current state of research on the potential relationship between protein content in human saliva and dental caries, which remains among the most common oral diseases and causes irreversible damage in the oral cavity. An understanding the whole saliva proteome in the oral cavity could serve as a prerequisite to obtaining insight into the etiology of tooth decay at early stages. To date, however, there is no comprehensive evidence showing that salivary proteins could serve as potential indicators for the early diagnosis of the risk factors causing dental caries. Therefore, proteomics indicates the promising direction of future investigations of such factors, including diagnosis and thus prevention in dental therapy.

scholarly journals A bibliometric study of research pertaining to the oldest-old (age eighty-five and older)

2020 ◽  
Vol 108 (1) ◽  
Author(s):  
Brady Daniel Lund ◽  
Ting Wang
Keyword(s):  
Information Science ◽  
Oldest Old ◽  
Bibliometric Study ◽  
Library And Information Science ◽  
Microsoft Excel ◽  
Current State ◽  
Visualization Software ◽  
Bibliographic Data ◽  
State Of Research ◽  
To Come

Objective: This bibliometric study investigated literature pertaining to a quickly growing population worldwide: the oldest-old, individuals age eighty-five and older. The current state of research was surveyed, based on top authors, publishers, authorship networks, themes in publication titles and abstracts, and highly cited publications.Methods: Bibliographic data was abstracted from the Web of Science database. Microsoft Excel was used for data analyses related to top author, publishers, and terms. VosViewer bibliographic visualization software was used to identify authorship networks.Results: Publications pertaining to the oldest-old have increased dramatically over the past three decades. The majority of these publications are related to medical or genetics topics. Citations for these publications remain relatively low but may be expected to grow in coming years, based on the publication behavior about and increasing prominence of this population. Claudio Franceschi and the Journal of the American Geriatrics Society were found to be the author and journal with the most publications pertaining to the oldest-old, respectively.Conclusions: The oldest-old is a population of rapidly growing significance. Researchers in library and information science, gerontology, and beyond can benefit themselves and those they serve by participating in research and specialized services to marginalized populations like the oldest-old. This bibliometric study hopefully serves as a launch-point for further inquiry and research in the years to come.

scholarly journals Using Google Maps to Show the Pattern of International Co-Author Collaboration in Pharmaceutics

2018 ◽  
pp. 1-9
Keyword(s):  
Drug Delivery ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Graphical Representations ◽  
Deep Insight ◽  
Microsoft Excel ◽  
Google Maps ◽  
Future Studies ◽  
Insight Into

Objective: To understand international co-author collaboration in pharmaceutics and to visualize results by Google maps and social network analysis (SNA). Methods: Selecting 311 abstracts from the Medline based on keyword pharmaceutics [journal], we reported following features of pharmaceutics: (1) nation distribution across continents; (2) main keywords frequently displayed in papers; (3) the eminent author in pharmaceutics. We programmed Microsoft Excel VBA for extracting data from Medline. Google Maps and SNA Pajek software show graphical representations of pharmaceutics. Results: We found that (1) the most number of papers in nations are from U.S.(81, 16.05%) and Japan(34, 10.93%); (2) the most linked keywords are Pharmacokinetics and drug delivery; (3) the eminent authors are Muhammad Sohail Arshad(UK) and Takeshi Yokoo(Japan). Conclusion: Social network analysis provides wide and deep insight into relationships of entities we interested. The results drawn from Google maps can provide more information to future studies in academics.

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

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.

scholarly journals Using Kano diagrams to display the most cited article types, affiliated countries, authors and MeSH terms on spinal surgery in recent 12 years

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Po-Hsin Chou ◽  
Yu-Tsen Yeh ◽  
Wei-Chih Kan ◽  
Tsair-Wei Chien ◽  
Shu-Chun Kuo
Keyword(s):  
Impact Factor ◽  
Spinal Surgery ◽  
Scientific Productivity ◽  
The United States ◽  
Mesh Term ◽  
Medical Subject Headings ◽  
Productive Author ◽  
Mesh Terms ◽  
The Us ◽  
European Spine Journal

Abstract Background Citation analysis has been increasingly applied to assess the quantity and quality of scientific research in various fields worldwide. However, these analyses on spinal surgery do not provide visualization of results. This study aims (1) to evaluate the worldwide research citations and publications on spinal surgery and (2) to provide visual representations using Kano diagrams onto the research analysis for spinal surgeons and researchers. Methods Article abstracts published between 2007 and 2018 were downloaded from PubMed Central (PMC) in 5 journals, including Spine, European Spine Journal, The Spine Journal, Journal of Neurosurgery: Spine, and Journal of Spinal Disorders and Techniques. The article types, affiliated countries, authors, and Medical subject headings (MeSH terms) were analyzed by the number of article citations using x-index. Choropleth maps and Kano diagrams were applied to present these results. The trends of MeSH terms over the years were plotted and analyzed. Results A total of 18,808 publications were extracted from the PMC database, and 17,245 were affiliated to countries/areas. The 12-year impact factor for the five spine journals is 5.758. We observed that (1) the largest number of articles on spinal surgery was from North America (6417, 37.21%). Spine earns the highest x-index (= 82.96). Comparative Study has the highest x-index (= 66.74) among all article types. (2) The United States performed exceptionally in x-indexes (= 56.86 and 44.5) on both analyses done on the total 18,808 and the top 100 most cited articles, respectively. The most influential author whose x-index reaches 15.11 was Simon Dagenais from the US. (3) The most cited MeSH term with an x-index of 23.05 was surgery based on the top 100 most cited articles. The most cited article (PMID = 18164449) was written by Dagenais and his colleagues in 2008. The most productive author was Michael G. Fehlings, whose x-index and the author's impact factor are 13.57(= √(13.16*14)) and 9.86(= 331.57/33.64), respectively. Conclusions There was a rapidly increasing scientific productivity in the field of spinal surgery in the past 12 years. The US has extraordinary contributions to the publications. Furthermore, China and Japan have increasing numbers of publications on spinal surgery. This study with Kano diagrams provides an insight into the research for spinal surgeons and researchers.

scholarly journals Two Similarity Metrics for Medical Subject Headings (MeSH): An Aid to Biomedical Text Mining and Author Name Disambiguation

2016 ◽  
Author(s):  
Neil R Smalheiser ◽  
Gary Bonifield
Keyword(s):  
Scientific Discovery ◽  
Semantic Relatedness ◽  
Mesh Term ◽  
The Body ◽  
Similarity Metrics ◽  
Name Disambiguation ◽  
Medical Subject Headings ◽  
Mesh Terms ◽  
Author Name Disambiguation ◽  
Subject Headings

In the present paper, we have created and characterized several similarity metrics for relating any two Medical Subject Headings (MeSH terms) to each other. The article-based metric measures the tendency of two MeSH terms to appear in the MEDLINE record of the same article. The author-based metric measures the tendency of two MeSH terms to appear in the body of articles written by the same individual (using the 2009 Author-ity author name disambiguation dataset as a gold standard). The two metrics are only modestly correlated with each other (r = 0.50), indicating that they capture different aspects of term usage. The article-based metric provides a measure of semantic relatedness, and MeSH term pairs that co-occur more often than expected by chance may reflect relations between the two terms. In contrast, the author metric is indicative of how individuals practice science, and may have value for author name disambiguation and studies of scientific discovery. We have calculated article metrics for all MeSH terms appearing in at least 25 articles in MEDLINE (as of 2014) and author metrics for MeSH terms published as of 2009. The dataset is freely available for download and can be queried at http://arrowsmith.psych.uic.edu/arrowsmith_uic/mesh_pair_metrics.html.

scholarly journals Rediscovering Psilocybin as an Antidepressive Treatment Strategy

2021 ◽  
Vol 14 (10) ◽  
pp. 985
Author(s):  
Rene Zeiss ◽  
Maximilian Gahr ◽  
Heiko Graf
Keyword(s):  
Psychiatric Treatment ◽  
Therapeutic Potential ◽  
Future Research ◽  
Current State ◽  
Controversial Topic ◽  
State Of Research ◽  
Antidepressive Treatment ◽  
High Treatment ◽  
Insight Into

There has recently been a renewal of interest in psychedelic research on the use of psilocybin in psychiatric treatment and, in particular, for the treatment of major depressive disorder (MDD). Several state-of-the-art studies have provided new insight into the mechanisms of action of psilocybin and its therapeutic potential. Nevertheless, many questions remain unanswered. With this review, we provide an overview of the current state of research on the potential mechanisms of psilocybin, its antidepressant potential, and the associated risks and adverse effects, to provide an update on a controversial topic discussed in psychopharmacology. A database search was conducted in Medline including articles on psilocybin over the period of the last 20 years. Despite the promising progress in understanding the mechanisms of psilocybin, the exact antidepressive mechanism and the role of the psychedelic experience remain elusive. The studies included in this review found high treatment effect sizes for psilocybin as an antidepressant. However, the results must be regarded as preliminary due to several limitations. Although the current studies observed no severe adverse events, several questions regarding safety and utility remain and must be subject of future research.

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