Text mining of hypertension researches in the west Asia region: a 12-year trend analysis.
Mohammad RezapourMohsen YazdinejadFaezeh Rajabi KouchiMasoomeh Habibi BaghiZahra KhorramiMorteza Khavanin ZadehElmira PourbaghiHassan RezapourPublished in: Renal failure (2024)
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.
Keyphrases
- artificial intelligence
- machine learning
- blood pressure
- deep learning
- end stage renal disease
- risk factors
- chronic kidney disease
- newly diagnosed
- ejection fraction
- mental health
- systematic review
- metabolic syndrome
- coronary artery disease
- prognostic factors
- south africa
- peritoneal dialysis
- physical activity
- weight loss
- insulin resistance
- skeletal muscle
- glycemic control