The Use of hx-index to compare research achievements for ophthalmology authors in Mainland China, Hong Kong, and Taiwan since 2010

Thematic maps with scatter and 4-quadrant plots in R to identity dominant entities on schizophrenia in psychiatry since 2017: Bibliometric analysis

BACKGROUND

Schizophrenia affects more than 21 million people worldwide. There have been a number of articles published in the literature regarding schizophrenia. It is unclear which authors contributed the most to the field of schizophrenia. This study examines which article entities (affiliated countries, institutes, journals, and authors) earn the most research achievements (RAs) and whether keywords in articles are associated with the number of article citations.

METHODS

As of August 25, 2022, 20,606 abstracts published on schizophrenia in psychiatry since 2017 were retrieved from the WoS core collection (WoSCC). RAs were measured using the category, JIF, authorship, and L-index (CJAL) score. The follower-leading cluster algorithm (FLCA) was used to examine clusters of keywords associated with core concepts of research. There were 7 types of visualizations used to report the study results, including Sankey diagrams, choropleth maps, scatter charts, radar plots, and cluster plots. A hypothesis was examined that the mean number of citations for keywords could predict the number of citations for 100 top-cited articles(T100SCHZ).

RESULTS

The results indicate that the US (18861), Kings College London (U.S. (2572), Psychiatry (14603), and Kolanu Nithin (Australia) (9.88) had the highest CJAL scores in countries, institutes, departments, and authors, respectively. The journal of Schizophrenia Res had higher citations (19,017), counts (1681), and mean citations (11.31) in journals. There was a significant correlation between article citations and weighted keywords (F = 1471.74; P < .001).

CONCLUSION

Seven visualizations were presented to report the study results, particularly with thematic maps using scatter and 4-quadrant plots produced in R programming language. We recommend that more future bibliographical studies utilize CAJL scores and thematic maps to report their findings, not restrict themselves solely to schizophrenia in psychiatry as done in this study.

Analyzing the number of articles with network meta-analyses using chord diagrams and temporal heatmaps over the past 10 years: Bibliometric analysis

BACKGROUND

Network meta-analyses (NMAs) are statistical techniques used to synthesize data from multiple studies and compare the effectiveness of different interventions for a particular disease or condition. They have gained popularity in recent years as a tool for evidence-based decision making in healthcare. Whether publications in NMAs have an increasing trend is still unclear. This study aimed to investigate the trends in the number of NMA articles over the past 10 years when compared to non-NMA articles.

METHODS

The study utilized data from the Web of Science database, specifically searching for articles containing the term "meta-analysis" published between 2013 and 2022. The analysis examined the annual number of articles, as well as the countries, institutions, departments, and authors associated with the articles and the journals in which they were published. Ten different visualization techniques, including line charts, choropleth maps, chord diagrams, circle packing charts, forest plots, temporal heatmaps, impact beam plots, pyramid plots, 4-quadrant radar plots, and scatter plots, were employed to support the hypothesis that the number of NMA-related articles has increased (or declined) over the past decade when compared to non-NMA articles.

RESULTS

Our findings indicate that there was no difference in mean citations or publication trends between NMA and non-NMA; the United States, McMaster University (Canada), medical schools, Dan Jackson from the United Kingdom, and the Journal of Medicine (Baltimore) were among the leading entities; NMA ranked highest on the coword analysis, followed by heterogeneity, quality, and protocol, with weighted centrality degrees of 32.51, 30.84, 29.43, and 24.26, respectively; and the number of NMA-related articles had increased prior to 2020 but experienced a decline in the past 3 years, potentially due to being overshadowed by the intense academic focus on COVID-19.

CONCLUSION

It is evident that the number of NMA articles increased rapidly between 2013 and 2019 before leveling off in the years following. For researchers, policymakers, and healthcare professionals who are interested in evidence-based decision making, the visualizations used in this study may be useful.

The 95% control lines on both confirmed cases and days of infection with COVID-19 were applied to compare the impact on public health between 2020 and 2021 using the hT-index

BACKGROUND

COVID-19, the disease caused by the novel coronavirus, is now a worldwide pandemic. The number of infected people has continually increased, and currently, this pandemic continues to present challenges to public health. Scatter plots are frequently used to interpret the impact in relation to confirmed cases. However, the 95% confidence intervals are rarely given to the scatter plot. The objective of this study was to; Develop 95% control lines on daily confirmed cases and infected days for countries/regions in COVID-19 (DCCIDC) and; Examine their impacts on public health (IPH) using the hT-index.

METHODS

All relevant COVID-19 data were downloaded from GitHub. The hT-index, taking all DCCIDCs into account, was applied to measure the IPHs for counties/regions. The 95% control lines were proposed to highlight the outliers of entities in COVID-19. The hT-based IPHs were compared among counties/regions between 2020 and 2021 using the choropleth map and the forest plot. The features of the hT-index were explained using the line chart and the box plot.

RESULTS

The top 2 countries measured by hT-based IPHs were India and Brazil in 2020 and 2021. The outliers beyond the 95% confidence intervals were Hubei (China), with a lower hT-index favoring 2021 ( = 6.4 in 2021 vs 15.55 in 2020) and higher hT indices favoring 2021 in Thailand (28.34 vs 14,77) and Vietnam (27.05 vs 10.88). Only 3 continents of Africa, Asia, and Europe had statistically and significantly fewer DCCIDCs (denoted by the hT-index) in 2021. The hT-index generalizes the h-index and overcomes the disadvantage without taking all elements (e.g., DCCIDCs) into account in features.

CONCLUSIONS

The scatter plot combined with the 95% control lines was applied to compare the IPHs hit by COVID-19 and suggested for use with the hT-index in future studies, not limited to the field of public health as we did in this research.

A leading author of meta-analysis does not have a dominant contribution to research based on the CJAL score: Bibliometric analysis

BACKGROUND

There have been nearly 200 thousand meta-analysis articles indexed by web of science (WoS) since 2013. To date, a bibliometric analysis of leading authors of meta-analyses that contribute to the field has not been conducted. Analyzing trend patterns in article citations and comparing individual research achievements (IRAs) are required following the extraction of meta-analysis articles. Using trend analysis, this study aims to verify the hypotheses that; The leading author has a dominant research achievement and; Recent articles that deserve worth reading can be identified.

METHODS

In the WoS collection, we identified the top 20 authors with the most articles related to meta-analysis. Using coword analysis, 2882 articles were collected to cluster author collaborations and identify the top 3 authors with the highest weighted centrality degrees. Based on the CJAL (category, journal raking by impact factor, authorship, and L-index on article citation) score and absolute advantage coefficient (AAC), we compared the IRAs and identified the author who dominated the field significantly beyond the next 2 authors. In WoS collection, coword analysis was used to highlight the characteristics of research domains for the top authors contributing to meta-analyses. The selection of articles that deserve reading is based on a temporal heatmap.

RESULTS

The top 2 authors were Young-Ho Lee (South Korea), Patompong Ungprasert (U.S.), and Brendon Stubbs (US) with CJAL scores of 240.71, 230.99, and 240.71, respectively. Based on the weak dominance coefficient (AAC = 0.49 < 0.50), it is evident that the leading meta-analysis author does not possess a significant dominant position over the next 2 leading authors in IRAs. Coword analysis was used to illustrate the characteristics of the 3 authors research domains. The 3 articles worth reading were selected based on a trend analysis of the last 4 years using the temporal heatmap.

CONCLUSION

A coword analysis of meta-analysis studies identified 3 leading authors. There was no evidence that 1 author possessed a dominant position due to the lower AAC (=0.49 < 0.50) for the leading author. As we have demonstrated in this study, the CJAL score and the AAC can be applied to many bibliographical studies in the future.

Classification and citation analysis of the 100 top-cited articles on nurse resilience using chord diagrams: A bibliometric analysis

BACKGROUND

Studies of most-cited articles have been frequently conducted on various topics and in various medical fields. To date, no study has examined the characteristics of articles associated with theme classifications and research achievements of article entities related to nursing resilience. This study aims to graphically depict the characteristics of the 100 top-cited articles addressing nurse resilience (T100NurseR), diagram the relationship between articles and author collaborations according to themes extracted from article keywords, and examine whether article keywords are correlated with article citations.

METHODS

T100NurseR publications were retrieved from the Web of Science (WoS) core collection on October 13, 2022. Themes associated with articles were explored using coword analysis in WoS keywords plus. The document category, journal ranking based on impact factor, authorship, and L-index and Y-index were used to analyze the dominant entities. To report the themes of T100NurseR and their research achievements in comparison to article entities and verify the hypothesis that keyword mean citation can be used to predict article citations, 5 visualizations were applied, including network diagrams, chord diagrams, dot plots, Kano diagrams, and radar plots.

RESULTS

Citations per article averaged 61.96 (range, 25-514). There were 5 themes identified in T100NurseR, including Parses theory, nurse resilience, conflict management, nursing identity, and emotional intelligence. For countries, institutes, departments, and authors in comparison of category, journal impact factor, authorship, and L-index scores, Australia (129.80), the University of Western Sydney (23.12), Nursing (87.17), and Kim Foster (23.76) are the dominant entities. The weighted number of citations according to Keywords Plus in WoS is significantly correlated with article citations (Pearson R = 0.94; P = .001).

CONCLUSION

We present diagrams to guide evidence-based clinical decision-making in nurse resilience based on the characteristics of the T100NurseR articles. Article citations can be predicted using weighted keywords. Future bibliographical studies may apply the 5 visualizations to relevant studies, not being solely restricted to T100NurseR.

Analysis of citation trends to identify articles on delirium worth reading using DDPP model with temporal heatmaps (THM): A bibliometric analysis

BACKGROUND

Delirium is one of the most common geriatric syndromes in older patients, accounting for 25% of hospitalized older patients, 31 to 35% of patients in the intensive care unit, and 8% to 17% of older patients in the emergency department (ED). A number of articles have been published in the literature regarding delirium. However, it is unclear about article citations evolving in the field. This study proposed a temporal heatmap (THM) that can be applied to all bibliographical studies for a better understanding of cited articles worth reading.

METHODS

As of November 25, 2022, 11,668 abstracts published on delirium since 2013 were retrieved from the Web of Science core collection. Research achievements were measured using the CJAL score. Social network analysis was applied to examine clusters of keywords associated with core concepts of research. A THM was proposed to detect articles worth reading based on recent citations that are increasing. The 100 top-cited articles related to delirium were displayed on an impact beam plot (IBP).

RESULTS

The results indicate that the US (12474), Vanderbilt University (US) (634), Anesthesiology (2168), and Alessandro Morandi (Italy) (116) had the highest CJAL scores in countries, institutes, departments, and authors, respectively. Articles worthy of reading were highlighted on a THM and an IBP when an increasing trend of citations over the last 4 years was observed.

CONCLUSION

The THM and IBP were proposed to highlight articles worth reading, and we recommend that more future bibliographical studies utilize the 2 visualizations and not restrict them solely to delirium-related articles in the future.

Using temporal heatmaps to identify worthwhile articles on immune checkpoint blockade for melanoma (ICBM) in Mainland China, Hong Kong, and Taiwan since 2000: A bibliometric analysis

BACKGROUND

Melanoma is a life-threatening form of skin cancer. Due to its remarkable effectiveness, the immune checkpoint blockade is widely used to treat melanoma (ICBM). No research has been conducted on ICBM for identifying the most readable articles. A bibliometric analysis of 100 top-cited ICBM (T100ICBM) in recent decades is required to highlight articles worth reading.

METHODS

Based on the Web of Science Core Collection, we summarized the articles on ICBM published in each year from 2000 to 2022, with first authors from Mainland China, Hong Kong, and Taiwan (CHT). Using the CJAL score, data extraction and visualization of the distribution of ICBM publications were conducted on 2718, and 100 top-cited articles, respectively. We used the temporal heatmap to identify the most readable articles. Four descriptive, diagnostic, predictive, and prescriptive analytics (called DDPP model) were applied to describe the features of T100ICBM articles. The absolute advantage coefficient was used to determine the dominance extent of the most influential region, institute, department, and author.

RESULTS

A total of 2718 publications was included after removing first or corresponding authors who were not affiliated with CHT. Publications by year showed a sharp increase from 2014 onward and either peaked in 2022 or have not yet peaked. It was evident that there was a large difference between the number of publications in provinces/metropolitan cities/regions on CHT. Beijing, Sichuan University, Oncology, and Guo Jun from Beijing are the most prolific and influential region, institute, department, and author. When comparing research achievements to the next productive authors based on the CJAL score, only Dr Jun has a medium effect of dominance (=0.60). On the basis of their consecutive growth in citations over the past 4 years, 20 T100ICBM articles were recommended for readers.

CONCLUSION

The field of ICBM is growing rapidly, and Beijing and Sichuan University are taking the lead in CHT. Furthermore, the study provides references for worth-reading articles using the temporal heatmap. Future research hot spots may focus on these 4 themes of immunotherapy, melanoma, metastatic melanoma, regulatory T cells, cells, and activation, which may pave the way for additional study.

Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis

BACKGROUND

We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT.

METHODS

Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords.

RESULTS

We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs.

CONCLUSION

Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.

Thematic analysis of articles on artificial intelligence with spine trauma, vertebral metastasis, and osteoporosis using chord diagrams: A systematic review and meta-analysis

BACKGROUND

Spine trauma, vertebral metastases, and osteoporosis (SVO) can result in serious health problems. If the diagnosis of SVO is delayed, the prognosis may be deteriorated. The use of artificial intelligence (AI) is an essential method for minimizing the diagnostic errors associated with SVO. research achievements (RAs) of SVO on AI are required as a result of the greatest number of studies on AI solutions reported. The study aimed to: classify article themes using visualizations, illustrate the characteristics of SVO on AI recently, compare RAs of SVO on AI between entities (e.g., countries, institutes, departments, and authors), and determine whether the mean citations of keywords can be used to predict article citations.

METHODS

A total of 31 articles from SVO on AI (denoted by T31SVOAI) have been found in Web of Science since 2018. The dominant entities were analyzed using the CJAL score and the Y-index. Five visualizations were applied to report: the themes of T31SVOAI and their RAs in comparison for article entities and verification of the hypothesis that the mean citations of keywords can predict article citations, including: network diagrams, chord diagrams, dot plots, a Kano diagram, and radar plots.

RESULTS

There were five themes classified (osteoporosis, personalized medicine, fracture, deformity, and cervical spine) by a chord diagram. The dominant entities with the highest CJAL scores were the United States (22.05), the University of Pennsylvania (5.72), Radiology (6.12), and Nithin Kolanu (Australia) (9.88). The majority of articles were published in Bone, J. Bone Miner. Res., and Arch. Osteoporos., with an equal count (=3). There was a significant correlation between the number of article citations and the number of weighted keywords (F = 392.05; P < .0001).

CONCLUSION

A breakthrough was achieved by displaying the characteristics of T31SVOAI using the CJAL score, the Y-index, and the chord diagram. Weighted keywords can be used to predict article citations. The five visualizations employed in this study may be used in future bibliographical studies.

The use of the time-to-event index (Tevent) to compare the negative impact of COVID-19 on public health among continents/regions in 2020 and 2021: An observational study

BACKGROUND

During the COVID-19 pandemic, how to measure the negative impact caused by COVID-19 on public health (ImpactCOV) is an important issue. However, few studies have applied the bibliometric index, taking both infected days (quantity) and impact (damage) into account for evaluating ImpactCOV thus far. This study aims to verify the proposed the time-to-event index (Tevent) that is viable and applicable in comparison with 11 other indicators, apply the Tevent to compare the ImpactCOVs among groups in continents/countries in 2020 and 2021, and develop an online algorithm to compute the Tevent-index and draw the survival analysis.

METHODS

We downloaded COVID-19 outbreak data of daily confirmed cases (DCCs) for all countries/regions. The Tevent-index was computed for each country and region. The impactCOVs among continents/countries were compared using the Tevemt indices for groups in 2020 and 2021. Three visualizations (i.e., choropleth maps, forest plot, and time-to-event, a.k.a. survival analysis) were performed. Online algorithms of Tevent as a composite score to denote the ImpactCOV and comparisons of Tevents for groups on Google Maps were programmed.

RESULTS

We observed that the top 3 countries affected by COVID-19 in 2020 and 2021 were (India, Brazil, Russia) and (Brazil, India, and the UK), respectively; statistically significant differences in ImpactCOV were found among continents; and an online time-event analysis showed Hubei Province (China) with a Tevent of 100.88 and 6.93, respectively, in 2020 and 2021.

CONCLUSION

The Tevent-index is viable and applicable to evaluate ImpactCOV. The time-to-event analysis as a branch of statistics for analyzing the expected duration of time until 1 event occurs is recommended to compare the difference in Tevent between groups in future research, not merely limited to ImpactCOV.

The use of radar plots with the Yk-index to identify which authors contributed the most to the journal of Medicine in 2020 and 2021: A bibliometric analysis

BACKGROUND

A consensus exists that the first author and corresponding author make the most contribution to the publication of an article. The Y-index has been proposed to assess the scientific achievements of authors, institutions, and countries/regions (AIC/R for short) based on the number of first-author publications (FPs) and corresponding-author publications (RPs). Nonetheless, the Y-index is defined in terms of count and radian (represented by j and h) instead of using the relative radius and angle degree to simplify understanding. In the literature, a method for drawing radar diagrams online with the Y-index is also lacking. This study was conducted to enhance the Y-index with an additional relative radius denoted by k and the angle degree represented by h* (named Yk-index), include easy-to-use features (e.g., copying and pasting) for the delivery of the online Radar-Yk, and identify which one of AIC/R contributed the most to a scientific journal.

METHODS

From the Web of Science (WoS) database, we downloaded 9498 abstracts of articles published in the journal of Medicine (Baltimore) in 2020 and 2021. Three visual representations were used, including a Sankey diagram, a choropleth map, and a radar diagram, to identify the characteristics of contributions by AIC/R to Medicine (Baltimore) using the Yk-index (j, k, h*). A demonstration of Rada-Yk with easy-to-use features was given using the copy-and-paste technique.

RESULTS

We found that Qiu Chen (China), Sichuan University (China), China, and South Korea (based on regions, e.g., provinces/metropolitan areas in China) were the most productive AIC/R, with their Yk equal to 27,715, 12415.1, and 2045, respectively; a total of 85.6% of the published articles in Medicine (Baltimore) came from the 3 countries (China, South Korea, and Japan); and this method of drawing the Radar-Yk online was provided and successfully demonstrated.

CONCLUSION

A breakthrough was achieved by developing the online Radar-Yk to show the most contributions to Medicine (Baltimore). Visualization of Radar-Yk could be replicated for future academic research and applications on other topics in future bibliographical studies.

A comparison of 3 productive authors' research domains based on sources from articles, cited references and citing articles using social network analysis

BACKGROUND

An individual's research domain (RD) can be determined from objective publication data (e.g., medical subject headings and Medical Subject Headings (MeSH) terms) by performing social network analysis. Bibliographic coupling (such as cocitation) is a similarity metric that relies on citation analysis to determine the similarity in RD between 2 articles. This study compared RD consistency between articles as well as their cited references and citing articles (ARCs).

METHODS

A total of 1388 abstracts were downloaded from PubMed and authored by 3 productive authors. Based on the top 3 clusters in social network analysis, similarity in RD was observed by comparing their consistency using the major MeSH terms in author articles, cited references and citing articles (ARC). Impact beam plots with La indices were drawn and compared for each of the 3 authors.

RESULTS

Sung-Ho Jang (South Korea), Chia-Hung Kao (Taiwan), and Chin-Hsiao Tseng (Taiwan) published 445, 780, and 163 articles, respectively. Dr Jang's RD is physiology, and Dr Kao and Dr Tseng's RDs are epidemiology. We confirmed the consistency of the RD terms by comparing the major MeSH terms in the ARC. Their La indexes were 5, 5, and 6, where a higher value indicates more extraordinary research achievement.

CONCLUSION

RD consistency was confirmed by comparing the main MeSH terms in ARC. The 3 approaches of RD determination (based on author articles, the La index, and the impact beam plots) were recommended for bibliographical studies in the future.

Authors who contributed most to the fields of hemodialysis and peritoneal dialysis since 2011 using the hT-index: Bibliometric analysis

BACKGROUND

The h-index does not take into account the full citation list of a researcher to evaluate individual research achievements (IRAs). As a generalization of the h-index, the hT-index takes all citations into account to evaluate IRAs. Compared to other bibliometric indices, it is unclear whether the hT-index is more closely associated with the h-index. We utilized articles published on hemodialysis and peritoneal dialysis (HD/PD) to validate the hT-index as a measure of the most significant contributions to HD/PD.

METHODS

Using keywords involving HD/PD in titles, subject areas, and abstracts since 2011, we obtained 7702 abstracts and their associated metadata (e.g., citations, authors, research institutes, countries of origin). In total, 4752 first or corresponding authors with hT-indices >0 were evaluated. To present the author's IRA, the following 4 visualizations were used: radar, Sankey, impact beam plot, and choropleth map to investigate whether the hT-index was more closely associated with the h-index than other indices (e.g., g-/x-indices and author impact factors), whether the United States still dominates the majority of publications concerning PD/HD, and whether there was any difference in research features between 2 prolific authors.

RESULTS

In HD/PD articles, we observed that (a) the hT-index was closer to and associated with the h-index; (b1) the United States (37.15), China (34.63), and Japan (28.09) had the highest hT-index; (b2) Sun Yat Sen University (Chian) earned the highest hT-index (=20.02) among research institutes; (c1) the authors with the highest hT-indices (=15.64 and 14.39, respectively) were David W Johnson (Australia) and Andrew Davenport (UK); and (c2) their research focuses on PD and HD, respectively.

CONCLUSION

The hT-index was demonstrated to be appropriate for assessing IRAs along with visualizations. The hT-index is recommended in future bibliometric analyses of IRAs as a complement to the h-index.

Using the Sankey diagram to visualize article features on the topics of whole-exome sequencing (WES) and whole-genome sequencing (WGS) since 2012: Bibliometric analysis

BACKGROUND

Sequencing technologies, such as whole-exome sequencing (WES) and whole-genome sequencing (WGS), have been increasingly applied to medical research in recent years. Which countries, journals, and institutes (called entities) contributed most to the fields (WES/WGS) remains unknown. Temporal bar graphs (TBGs) are frequently used in trend analysis of publications. However, how to draw the TBG on the Sankey diagram is not well understood in bibliometrics. We thus aimed to investigate the evolution of article entities in the WES/WGS fields using publication-based TBGs and compare the individual research achievements (IRAs) among entities.

METHODS

A total of 3599 abstracts downloaded from icite analysis were matched to entities, including article identity numbers, citations, publication years, journals, affiliated countries/regions of origin, and medical subject headings (MeSH terms) in PubMed on March 12, 2022. The relative citation ratio (RCR) was extracted from icite analysis to compute the hT index (denoting the IRA, taking both publications and citations into account) for each entity in the years between 2012 and 2021. Three types of visualizations were applied to display the trends of publications (e.g., choropleth maps and the enhanced TBGs) and IRAs (e.g., the flowchart on the Sankey diagram) for article entities in WES/WGS.

RESULTS

We observed that the 3 countries (the US, China, and the UK) occupied most articles in the WES/WGS fields since 2012, the 3 entities (i.e., top 5 journals, research institutes, and MeSH terms) were demonstrated on the enhanced TBGs, the top 2 MeSH terms were genetics and methods in WES and WGS, and the IRAs of 6 article entities with their hT-indices were succinctly and simultaneously displayed on a single Sankey diagram that was never launched in bibliographical studies.

CONCLUSION

The number of WES/WGS-related articles has dramatically increased since 2017. TBGs, particularly with hTs on the Sankey, are recommended for research on a topic (or in a discipline) to compare trends of publications and IRAs for entities in future bibliographical studies.