Medical informatics and bioinformatics: a bibliometric study

Analysis of Persian Bioinformatics Research with Topic Modeling

Purpose

As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively.

Conclusion

The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other.

Global Scientific Research Landscape on Medical Informatics From 2011 to 2020: Bibliometric Analysis

Background

With the emerging information and communication technology, the field of medical informatics has dramatically evolved in health care and medicine. Thus, it is crucial to explore the global scientific research landscape on medical informatics.

Objective

This study aims to present a visual form to clarify the overall scientific research trends of medical informatics in the past decade.

Methods

A bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database was performed to analyze global scientific research trends on medical informatics, including publication year, journals, authors, institutions, countries/regions, references, and keywords, from January 1, 2011, to December 31, 2020.

Results

The data set recorded 34,742 articles related to medical informatics from WoSCC between 2011 and 2020. The annual global publications increased by 193.86% from 1987 in 2011 to 5839 in 2020. Journal of Medical Internet Research (3600 publications and 63,932 citations) was the most productive and most highly cited journal in the field of medical informatics. David W Bates (99 publications), Harvard University (1161 publications), and the United States (12,927 publications) were the most productive author, institution, and country, respectively. The co-occurrence cluster analysis of high-frequency author keywords formed 4 clusters: (1) artificial intelligence in health care and medicine; (2) mobile health; (3) implementation and evaluation of electronic health records; (4) medical informatics technology application in public health. COVID-19, which ranked third in 2020, was the emerging theme of medical informatics.

Conclusions

We summarize the recent advances in medical informatics in the past decade and shed light on their publication trends, influential journals, global collaboration patterns, basic knowledge, research hotspots, and theme evolution through bibliometric analysis and visualization maps. These findings will accurately and quickly grasp the research trends and provide valuable guidance for future medical informatics research.

Evaluating the outcomes of medical informatics development as a discipline in China: A publication perspective

BACKGROUND

As the world's second largest economy, China makes unique contributions to the world in many fields, including sociology, the economy, technology and defense. Medical informatics (MI) is an important cross-disciplinary field that, along with its applications, has received massive funding from the Chinese government. However, the question of how to evaluate China's input and output in MI remains important and complex issue of great significance for China and the rest of the world.

OBJECTIVE

This paper analyzed, for the first time, the quality and quantity of research by Chinese academics in MI based on their articles published in international specialty journals in recent years and examined MI research hotspots in China. Our purpose is to summarize the experiences and lessons learned by China and the rest of the world as they develop MI.

METHOD

We targeted 18 MI journals listed in the JCR 2016 report and searched for papers published by Chinese academics in these 18 journals in the WOS and PUBMED databases and on journal sites. We also performed data cleansing and categorized the obtained information. We used Excel, SPSS, Ucinet and NetDraw to conduct quantitative analyses on the research papers.

RESULTS

A total of 1340 articles satisfied the inclusion criteria of this study. We observed a significant upward trend in the number of articles published over time, particularly after 2011. Lei Jianbo, Huang Zhengxing and Li Jin-song are active Chinese authors in the MI discipline who have written many high-quality publications. Meanwhile, universities remain the primary breeding grounds for scientific research: 93.36% of the articles came from universities. Zhejiang University published the most first-author articles, whereas Zhejiang University, Shanghai Jiao Tong University and Tsinghua University produced 17.76% of the total articles. According to the lists of authors, 24% of the papers were co-authored with foreign researchers. This rate of cooperation is increasing each year, from 5.88% to the current rate of 39.04%. An analysis of keywords showed that "EMR", "SVM", "Authentication", "Telecare medical information system", "EEG", "ECG" and "RFID" were the most frequently searched terms in popular technological fields, including artificial intelligence and image processing. In recent years, there has been a significant increase in the number of high-frequency keywords and a broadening range of research fields, which has led to the emergence of several research hotspots, including MI systems, mobile health care, telecare, data mining and machine learning.

CONCLUSIONS

Through the quantitative analysis of publications, we discovered the emergence of three stages - infancy, slow growth and rapid growth - in China's MI research in recent years as academics make achievements in their research works. The global influence of Chinese academics is growing, and they are making increasingly conscious efforts to enter into research collaborations with foreign researchers. The findings of Chinese academics' publications are gaining international recognition.

Longitudinal trends in global obesity research and collaboration: a review using bibliometric metadata

The goal of this study was to understand research trends and collaboration patterns together with scholarly impact within the domain of global obesity research. We developed and analysed bibliographic affiliation data collected from 117,340 research articles indexed in Scopus database on the topic of obesity and published from 1993-2012. We found steady growth and an exponential increase of publication numbers. Research output in global obesity research roughly doubled each 5 years, with almost 80% of the publications and authors from the second decade (2003-2012). The highest publication output was from the USA - 42% of publications had at least one author from the USA. Many US institutions also ranked highly in terms of research output and collaboration. Fifteen of the top-20 institutions in terms of publication output were from the USA; however, several European and Japanese research institutions ranked more highly in terms of average citations per paper. The majority of obesity research and collaboration has been confined to developed countries although developing countries have showed higher growth in recent times, e.g. the publication ratio between 2003-2012 and 1993-2002 for developing regions was much higher than that of developed regions (9:1 vs. 4:1). We also identified around 42 broad disciplines from authors' affiliation data, and these showed strong collaboration between them. Overall, this study provides one of the most comprehensive longitudinal bibliometric analyses of obesity research. This should help in understanding research trends, spatial density, collaboration patterns and the complex multi-disciplinary nature of research in the obesity domain.

*informatics: Identifying and Tracking Informatics Sub-Discipline Terms in the Literature

OBJECTIVE

To identify the breadth of informatics sub-discipline terms used in the literature for enabling subsequent organization and searching by sub-discipline.

METHODS

Titles in five literature sources were analyzed to extract terms for informatics sub-disciplines: 1) United States (U.S.) Library of Congress Online Catalog, 2) English Wikipedia, 3) U.S. National Library of Medicine (NLM) Catalog, 4) PubMed, and 5) PubMed Central. The extracted terms were combined and standardized with those in four vocabulary sources to create an integrated list: 1) Library of Congress Subject Headings (LCSH), 2) Medical Subject Headings (MeSH), 3) U.S. National Cancer Institute Thesaurus (NCIt), and 4) EMBRACE Data and Methods (EDAM). Searches for terms in titles from each literature source were conducted to obtain frequency counts and start years for characterizing established and potentially emerging sub-disciplines.

RESULTS

Analysis of 6,949 titles from literature sources and 67 terms from vocabulary sources resulted in an integrated list of 382 terms for informatics sub-disciplines mapped to 292 preferred terms. In the last five decades, "bioinformatics", "medical informatics", "health informatics", "nursing informatics", and "biomedical informatics" were associated with the most literature. In the current decade, potentially emerging sub-disciplines include "disability informatics", "neonatal informatics", and "nanoinformatics" based on literature from the last five years.

CONCLUSIONS

As the field of informatics continues to expand and advance, keeping up-to-date with historical and current trends will become increasingly challenging. The ability to track the accomplishments and evolution of a particular sub-discipline in the literature could be valuable for supporting informatics research, education, and training.

Detecting evolution of bioinformatics with a content and co-authorship analysis

Bioinformatics is an interdisciplinary research field that applies advanced computational techniques to biological data. Bibliometrics analysis has recently been adopted to understand the knowledge structure of a research field by citation pattern. In this paper, we explore the knowledge structure of Bioinformatics from the perspective of a core open access Bioinformatics journal, BMC Bioinformatics with trend analysis, the content and co-authorship network similarity, and principal component analysis. Publications in four core journals including Bioinformatics - Oxford Journal and four conferences in Bioinformatics were harvested from DBLP. After converting publications into TF-IDF term vectors, we calculate the content similarity, and we also calculate the social network similarity based on the co-authorship network by utilizing the overlap measure between two co-authorship networks. Key terms is extracted and analyzed with PCA, visualization of the co-authorship network is conducted. The experimental results show that Bioinformatics is fast-growing, dynamic and diversified. The content analysis shows that there is an increasing overlap among Bioinformatics journals in terms of topics and more research groups participate in researching Bioinformatics according to the co-authorship network similarity.

e-MIR2: a public online inventory of medical informatics resources

BACKGROUND

Over the past years, the number of available informatics resources in medicine has grown exponentially. While specific inventories of such resources have already begun to be developed for Bioinformatics (BI), comparable inventories are as yet not available for the Medical Informatics (MI) field, so that locating and accessing them currently remains a difficult and time-consuming task.

DESCRIPTION

We have created a repository of MI resources from the scientific literature, providing free access to its contents through a web-based service. We define informatics resources as all those elements that constitute, serve to define or are used by informatics systems, ranging from architectures or development methodologies to terminologies, vocabularies, databases or tools. Relevant information describing the resources is automatically extracted from manuscripts published in top-ranked MI journals. We used a pattern matching approach to detect the resources' names and their main features. Detected resources are classified according to three different criteria: functionality, resource type and domain. To facilitate these tasks, we have built three different classification schemas by following a novel approach based on folksonomies and social tagging. We adopted the terminology most frequently used by MI researchers in their publications to create the concepts and hierarchical relationships belonging to the classification schemas. The classification algorithm identifies the categories associated with resources and annotates them accordingly. The database is then populated with this data after manual curation and validation.

CONCLUSIONS

We have created an online repository of MI resources to assist researchers in locating and accessing the most suitable resources to perform specific tasks. The database contains 609 resources at the time of writing and is available at http://www.gib.fi.upm.es/eMIR2. We are continuing to expand the number of available resources by taking into account further publications as well as suggestions from users and resource developers.

Visibility of medical informatics regarding bibliometric indices and databases

BACKGROUND

The quantitative study of the publication output (bibliometrics) deeply influences how scientific work is perceived (bibliometric visibility). Recently, new bibliometric indices and databases have been established, which may change the visibility of disciplines, institutions and individuals. This study examines the effects of the new indices on the visibility of Medical Informatics.

METHODS

By objective criteria, three sets of journals are chosen, two representing Medical Informatics and a third addressing Internal Medicine as a benchmark. The availability of index data (index coverage) and the aggregate scores of these corpora are compared for journal-related (Journal impact factor, Eigenfactor metrics, SCImago journal rank) and author-related indices (Hirsch-index, Egghes G-index). Correlation analysis compares the dependence of author-related indices.

RESULTS

The bibliometric visibility depended on the research focus and the citation database: Scopus covers more journals relevant for Medical Informatics than ISI/Thomson Reuters. Journals focused on Medical Informatics' methodology were negatively affected by the Eigenfactor metrics, while the visibility profited from an interdisciplinary research focus. The correlation between Hirsch-indices computed on citation databases and the Internet was strong.

CONCLUSIONS

The visibility of smaller technology-oriented disciplines like Medical Informatics is changed by the new bibliometric indices and databases possibly leading to suitably changed publication strategies. Freely accessible author-related indices enable an easy and adequate individual assessment.

Knowledge structure of korean medical informatics: a social network analysis of articles in journal and proceedings

Objectives

This study aimed at exploring the knowledge structure of Korean medical informatics.

Methods

We utilized the keywords, as the main variables, of the research papers that were presented in the journal and symposia of the Korean Society of Medical Informatics, and we used, as cases, the English titles and abstracts of the papers (n = 915) published from 1995 through 2008. N-grams (bigram to 5-gram) were extracted from the corpora using the BiKE Text Analyzer, and their cooccurrence networks were generated via a cosine correlation coefficient, and then the networks were analyzed and visualized using Pajek.

Results

With the hub and authority measures, the most important research topics in Korean medical informatics were identified. Newly emerging topics by three-year period units were observed as research trends.

Conclusions

This study provides a systematic overview on the knowledge structure of Korean medical informatics.

The role of endocarditis, myocarditis and pericarditis in qualitative and quantitative data analysis

The current study is the first scientometric analysis of research activity and output in the field of inflammatory disorders of the heart (endo-, myo- and pericarditis). Scientometric methods are used to compare scientific performance on national and on international scale to identify single areas of research interest. Interest and research productivity in inflammatory diseases of the heart have increased since 1990. The majority of publications about inflammatory heart disorders were published in Western Europe and North America. The United States of America had a leading position in terms of research productivity and quality; half of the most productive authors in this study came from American institutions. The analysis of international cooperation revealed research activity in countries that are less established in the field of inflammatory heart disorder research, such as Brazil, Saudi Arabia and Tunisia. These results indicate that future research of heart inflammation may no longer be influenced predominantly by a small number of countries. Furthermore, this study revealed weaknesses in currently established scientometric parameters (i.e., h-index, impact factor) that limit their suitability as measures of research quality. In this respect, self-citations should be generally excluded from calculations of h-index and impact factor.

An analysis of bibliometric indicators, National Institutes of Health funding, and faculty size at Association of American Medical Colleges medical schools, 1997-2007

OBJECTIVE

The objective of this study was to analyze bibliometric data from ISI, National Institutes of Health (NIH)-funding data, and faculty size information for Association of American Medical Colleges (AAMC) member schools during 1997 to 2007 to assess research productivity and impact.

METHODS

This study gathered and synthesized 10 metrics for almost all AAMC medical schools(n=123): (1) total number of published articles per medical school, (2) total number of citations to published articles per medical school, (3) average number of citations per article, (4) institutional impact indices, (5) institutional percentages of articles with zero citations, (6) annual average number of faculty per medical school, (7) total amount of NIH funding per medical school, (8) average amount of NIH grant money awarded per faculty member, (9) average number of articles per faculty member, and (10)average number of citations per faculty member. Using principal components analysis, the author calculated the relationships between measures, if they existed.

RESULTS

Principal components analysis revealed 3 major clusters of variables that accounted for 91% of the total variance: (1) institutional research productivity, (2) research influence or impact, and (3)individual faculty research productivity. Depending on the variables in each cluster, medical school research may be appropriately evaluated in a more nuanced way. Significant correlations exist between extracted factors, indicating an interrelatedness of all variables. Total NIH funding may relate more strongly to the quality of the research than the quantity of the research. The elimination of medical schools with outliers in 1 or more indicators (n=20)altered the analysis considerably.

CONCLUSIONS

Though popular, ordinal rankings cannot adequately describe the multidimensional nature of a medical school's research productivity and impact. This study provides statistics that can be used in conjunction with other sound methodologies to provide a more authentic view of a medical school's research. The large variance of the collected data suggests that refining bibliometric data by discipline, peer groups, or journal information may provide a more precise assessment.