Dataset Information

One Hundred Years of Hypertension Research: Topic Modeling Study.

ABSTRACT:

Background

Due to scientific and technical advancements in the field, published hypertension research has developed substantially during the last decade. Given the amount of scientific material published in this field, identifying the relevant information is difficult. We used topic modeling, which is a strong approach for extracting useful information from enormous amounts of unstructured text.

Objective

This study aims to use a machine learning algorithm to uncover hidden topics and subtopics from 100 years of peer-reviewed hypertension publications and identify temporal trends.

Methods

The titles and abstracts of hypertension papers indexed in PubMed were examined. We used the latent Dirichlet allocation model to select 20 primary subjects and then ran a trend analysis to see how popular they were over time.

Results

We gathered 581,750 hypertension-related research articles from 1900 to 2018 and divided them into 20 topics. These topics were broadly categorized as preclinical, epidemiology, complications, and therapy studies. Topic 2 (evidence review) and topic 19 (major cardiovascular events) are the key (hot topics). Most of the cardiopulmonary disease subtopics show little variation over time, and only make a small contribution in terms of proportions. The majority of the articles (414,206/581,750; 71.2%) had a negative valency, followed by positive (119, 841/581,750; 20.6%) and neutral valency (47,704/581,750; 8.2%). Between 1980 and 2000, negative sentiment articles fell somewhat, while positive and neutral sentiment articles climbed substantially.

Conclusions

The number of publications has been increasing exponentially over the period. Most of the uncovered topics can be grouped into four categories (ie, preclinical, epidemiology, complications, and treatment-related studies).

SUBMITTER: Abba M

PROVIDER: S-EPMC9161044 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

One Hundred Years of Hypertension Research: Topic Modeling Study.

Abba Mustapha M Nduka Chidozie C Anjorin Seun S Mohamed Shukri S Agogo Emmanuel E Uthman Olalekan O

JMIR formative research 20220518 5

<h4>Background</h4>Due to scientific and technical advancements in the field, published hypertension research has developed substantially during the last decade. Given the amount of scientific material published in this field, identifying the relevant information is difficult. We used topic modeling, which is a strong approach for extracting useful information from enormous amounts of unstructured text.<h4>Objective</h4>This study aims to use a machine learning algorithm to uncover hidden topics ...[more]

PMID: 35583933

Similar Datasets

Project description:BackgroundOne Health is particularly relevant to the Horn of Africa where many people's livelihoods are highly dependent on livestock and their shared environment. In this context, zoonoses may have a dramatic impact on both human and animal health, but also on country economies. This scoping review aimed to characterise and evaluate the nature of zoonotic disease research in the Horn region. Specifically, it addressed the following questions: (i) what specific zoonotic diseases have been prioritised for research, (ii) what data have been reported (human, animal or environment), (iii) what methods have been applied, and (iv) who has been doing the research?Methodology/principal findingsWe used keyword combinations to search online databases for peer-reviewed papers and theses. Screening and data extraction (disease, country, domain and method) was performed using DistillerSR. A total of 2055 studies focusing on seven countries and over 60 zoonoses were included. Brucellosis attracted the highest attention in terms of research while anthrax, Q fever and leptospirosis have been comparatively under-studied. Research efforts did not always align with zoonoses priorities identified at national levels. Despite zoonoses being a clear target for 'One Health' research, a very limited proportion of studies report data on the three domains of human, animal and environment. Descriptive and observational epidemiological studies were dominant and only a low proportion of publications were multidisciplinary. Finally, we found that a minority of international collaborations were between Global South countries with a high proportion of authors having affiliations from outside the Horn of Africa.Conclusions/significanceThere is a growing interest in zoonoses research in the Horn of Africa. Recommendations arising from this scoping review include: (i) ensuring zoonoses research aligns with national and global research agendas; (ii) encouraging researchers to adopt a holistic, transdisciplinary One Health approach following high quality reporting standards (COHERE, PRISMA, etc.); and (iii) empowering local researchers supported by regional and international partnerships to engage in zoonoses research.

Project description:BackgroundBeing diagnosed with cancer during childhood or adolescence can disrupt important periods in an individual's physical, psychosocial, and spiritual development and potentially reduce the quality of life (QOL) after treatment. Research is urgently required to improve the QOL for child and adolescent cancer survivors, and it is necessary to analyze the trends in prior research reported in international academic journals to identify knowledge structures.ObjectiveThis study aims to identify the main keywords based on network centrality, subgroups (clusters) of keyword networks by using a cohesion analysis method, and the main theme of child and adolescent cancer survivor-related research abstracts through topic modeling. This study also aims to label the subgroups by comparing the results of the cohesion and topic modeling.MethodsA text network analysis method and topic modeling were used to explore the main trends in child and adolescent cancer survivor research by structuring a network of keyword (semantic morphemes) co-occurrence in the abstracts of articles published in 5 major web-based databases from 2016 to 2020. A total of 1677 child and adolescent cancer survivor-related studies were used for data analyses. Data selection, processing, and analyses were also conducted.ResultsThe top 5 keywords in terms of degree and eigenvector centrality were risk, control interval, radiation, childhood cancer treatment, and diagnosis. Of the 1677 studies used for data analyses, cluster 1 included 780 (46.51%) documents under risk management, cluster 2 contained 557 (33.21%) articles under health-related QOL and supportive care, and cluster 3 consisted of 340 (20.27%) studies under cancer treatment and complications.ConclusionsThis study is significant in that it confirms the knowledge structure based on the main keywords and cross-disciplinary trends in child and adolescent cancer survivor research published in the last 5 years worldwide. The primary goal of child and adolescent cancer survivor research is to prevent and manage the various aspects of the problems encountered during the transition to a normal life and to improve the overall QOL. To this end, it is necessary to further revitalize the study of the multidisciplinary team approach for the promotion of age-specific health behaviors and the development of intervention strategies with increased feasibility for child and adolescent cancer survivors.

Project description:BackgroundWith the exponential growth of publications in the field of investigator-initiated research/trials (IIRs/IITs), it has become necessary to employ text mining and bibliometric analysis as tools for gaining deeper insights into this area of study. By using these methods, researchers can effectively identify and analyze research topics within the field.MethodsThis study retrieved relevant publications from the Web of Science Core Collection and conducted bioinformatics analysis. The latent Dirichlet allocation model, which is based on machine learning, was utilized to identify subfield research topics.ResultsA total of 4315 articles related to IIRs/IITs were obtained from the Web of Science Core Collection. After excluding duplicates and articles with missing abstracts, a final dataset of 3333 articles was included for bibliometric analysis. The number of publications showed a steady increase over time, particularly since 2000. The United States, Germany, the United Kingdom, the Netherlands, Canada, Denmark, Japan, Switzerland, and France emerged as the most productive countries in terms of IIRs/IITs. The citation analysis revealed intriguing trends, with certain highly cited articles showing a significant increase in citation frequency in recent years. A model with 45 topics was deemed the best fit for characterizing the extensively researched fields within IIRs/IITs. Our analysis revealed 10 top topics that have garnered significant attention, spanning domains such as community health, cancer treatment, brain development and disease mechanisms, nursing research, and stem cell therapy. These top topics offer researchers valuable directions for further investigation and innovation. Additionally, we identified 12 hot topics, which represent the most cutting-edge and highly regarded research areas within the field.ConclusionThis study contributes to a comprehensive understanding of the current research landscape and provides valuable insights for researchers working in this domain.

Dataset Information

One Hundred Years of Hypertension Research: Topic Modeling Study.

Background

Objective

Methods

Results

Conclusions

Publications

One Hundred Years of Hypertension Research: Topic Modeling Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets