Text mining of hypertension researches in the west Asia region: a 12-year trend analysis

Abstract

More than half of the world population lives in Asia and hypertension (HTN) is the most prevalent risk factor found in Asia. There are numerous articles published about HTN in Eastern Mediterranean Region (EMRO) and artificial intelligence (AI) methods can analyze articles and extract top trends in each country. Present analysis uses Latent Dirichlet allocation (LDA) as an algorithm of topic modeling (TM) in text mining, to obtain subjective topic-word distribution from the 2790 studies over the EMRO. The period of checked studied is last 12 years and results of LDA analyses show that HTN researches published in EMRO discuss on changes in BP and the factors affecting it. Among the countries in the region, most of these articles are related to I.R Iran and Egypt, which have an increasing trend from 2017 to 2018 and reached the highest level in 2021. Meanwhile, Iraq and Lebanon have been conducting research since 2010. The EMRO word cloud illustrates ‘BMI’, ‘mortality’, ‘age’, and ‘meal’, which represent important indicators, dangerous outcomes of high BP, and gender of HTN patients in EMRO, respectively.

Keywords:

• Chronic kidney disease
• hypertension
• artificial intelligence
• text mining
• trend detection

Author contributions

Conceptualizations, M.R. and M.Y.; methodology and software, M.R., M.Y., and F.R.K.; formal analysis, M.R., H.R., M.H.B., Z.K., E.P., and M.K.Z.; investigation, M.H.B., Z.K., and M.K.Z.; resources, M.R., H.R., and M.H.B.; data curation, M.Y. and F.R.K.; writing – original draft preparation, M.R., M.Y., and M.H.B.; writing – review and editing, M.R.; visualization, M.R., M.Y., and F.R.K.; supervision, M.R. and H.R; project administration. All authors have read and agreed to the published version of the manuscript.

Disclosure statement

The authors report no conflicts of interest. None of the authors have any financial relation with the online archive or software systems, used in this article.

Data availability statement

All cleaned and pre-processed data and/or analyzed during this research are available from the corresponding author on reasonable request, but the original articles are available online in PubMed.