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:: Volume 20, Issue 5 (Winter: special issue: Policy Brief 2026) ::
Iranian J Nutr Sci Food Technol 2026, 20(5): 209-212 Back to browse issues page
Implementation of an Intelligent Blood Pressure Screening System: A Novel Strategy for Improving Early Detection and Diagnosis of Hypertension in Iran
M Taheri Ghaleno * , F Zayeri , F Azizi , R Homayounfar
, melikataheri24@gmail.com
Abstract:   (16 Views)
Background and Aim: Hypertension, is a critical public health challenge in Iran, due to its asymptomatic nature. Delayed diagnosis of this disease leads to severe complications, including heart and kidney failure and stroke. Traditional screening lacks the sensitivity needed for an aging population and obesity epidemic.
Materials and Methods: This study used data from the Fasa Cohort Study including 9,951 rural participants, aged from 35 to70. Advanced machine learning algorithms, specifically the novel COZMOS algorithm and Random Forest models, were utilized to identify risk factors of hypertension and predict this disease in the cohort under study.
Findings: The prevalence of hypertension was 28.13% (33.69% in women; 21.31% in men). BMI, fasting blood sugar, and history of heart disease—which increases risk of hypertension by 4.61-fold—were key predictors. The Random Forest model achieved the highest accuracy (with an estimated AUC of 75.38%).
Conclusion: Smart screening systems should replace traditional tools. Integrating AI into Electronic Health Records (SIB) can enhance primary health care (PHC) detection and reduce non-communicable disease burden in our country.
Keywords: Classification tree, COZMOS algorithm, Random forest, Hypertension, FASA cohort study
Full-Text [PDF 652 kb]   (14 Downloads)    
Article type: Brief Policy | Subject: nutrition
Received: 2026/05/31 | Accepted: 2026/01/30 | Published: 2026/01/30
References
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Taheri Ghaleno M, Zayeri F, Azizi F, Homayounfar R. Implementation of an Intelligent Blood Pressure Screening System: A Novel Strategy for Improving Early Detection and Diagnosis of Hypertension in Iran. Iranian J Nutr Sci Food Technol 2026; 20 (5) :209-212
URL: http://nsft.sbmu.ac.ir/article-1-4168-en.html
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Volume 20, Issue 5 (Winter: special issue: Policy Brief 2026) Back to browse issues page
Iranian Journal of Nutrition Sciences and Food Technology
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