Text mining of hypertension researches in the west Asia region: a 12-year trend analysis
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...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Renal Failure |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2337285 |
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| _version_ | 1832591086315372544 |
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| author | Mohammad Rezapour Mohsen Yazdinejad Faezeh Rajabi Kouchi Masoomeh Habibi Baghi Zahra Khorrami Morteza Khavanin Zadeh Elmira Pourbaghi Hassan Rezapour |
| author_facet | Mohammad Rezapour Mohsen Yazdinejad Faezeh Rajabi Kouchi Masoomeh Habibi Baghi Zahra Khorrami Morteza Khavanin Zadeh Elmira Pourbaghi Hassan Rezapour |
| author_sort | Mohammad Rezapour |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-312bbd4060994e41914398ff178369d8 |
| institution | Kabale University |
| issn | 0886-022X 1525-6049 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj-art-312bbd4060994e41914398ff178369d82025-01-23T04:17:49ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492024-12-0146110.1080/0886022X.2024.2337285Text mining of hypertension researches in the west Asia region: a 12-year trend analysisMohammad Rezapour0Mohsen Yazdinejad1Faezeh Rajabi Kouchi2Masoomeh Habibi Baghi3Zahra Khorrami4Morteza Khavanin Zadeh5Elmira Pourbaghi6Hassan Rezapour7Faculty Member of the Iranian Ministry of Science, Research and Technology, Tehran, IranArtificial Intelligence, University of Isfahan, Isfahan, IranDepartment of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, IranDepartment of Educational Science, Shahid Beheshti University, Tehran, IranOphthalmic Epidemiology Research Center, Research Institute for Ophthalmology and Vision Science, Shahid Beheshti University of Medical Sciences, Tehran, IranHasheminejad Kidney Center, School of Medicine, Iran University of Medical Sciences, Tehran, IranFaculty of Advanced Sciences and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, IranDepartment of Transportation and Urban Infrastructure Studies, Morgan State University, Baltimore, MD, USAMore 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.https://www.tandfonline.com/doi/10.1080/0886022X.2024.2337285Chronic kidney diseasehypertensionartificial intelligencetext miningtrend detection |
| spellingShingle | Mohammad Rezapour Mohsen Yazdinejad Faezeh Rajabi Kouchi Masoomeh Habibi Baghi Zahra Khorrami Morteza Khavanin Zadeh Elmira Pourbaghi Hassan Rezapour Text mining of hypertension researches in the west Asia region: a 12-year trend analysis Renal Failure Chronic kidney disease hypertension artificial intelligence text mining trend detection |
| title | Text mining of hypertension researches in the west Asia region: a 12-year trend analysis |
| title_full | Text mining of hypertension researches in the west Asia region: a 12-year trend analysis |
| title_fullStr | Text mining of hypertension researches in the west Asia region: a 12-year trend analysis |
| title_full_unstemmed | Text mining of hypertension researches in the west Asia region: a 12-year trend analysis |
| title_short | Text mining of hypertension researches in the west Asia region: a 12-year trend analysis |
| title_sort | text mining of hypertension researches in the west asia region a 12 year trend analysis |
| topic | Chronic kidney disease hypertension artificial intelligence text mining trend detection |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2337285 |
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