Important predictors of high-risk for CVD.

<div><p>Background</p><p>Cardiovascular disease (CVD) encompasses a group of disorders that affect the heart and blood vessels, making it one of the leading causes of death globally, including in Bangladesh. Applying predictive modeling for the early identification and detect...

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Bibliographic Details
Main Author:	Md. Merajul Islam (12646837) (author)
Other Authors:	Sujit Kumar (7480604) (author), Md. A. Salam (22386223) (author), Dulal Chandra Roy (5421059) (author), Md. Rezaul Karim (7225511) (author)
Published:	2025
Subjects:	Medicine Biotechnology Sociology Cancer Virology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified targeted prevention strategies na &# 239 machine learning algorithms key factors contributing extreme gradient boosting body mass index association mining technique artificial neural network important features associated association rules identified applying predictive modeling enhancing prediction precision cardiovascular risk prediction recent bangladesh demographic including logistic regression boruta method indicated 22 %, precision 70 %, f1 richest wealth status evaluated using accuracy 54 %, significant rules predictive performance marital status important predictors analyzed using risk individuals xlink "> training dataset thereby facilitating testing set study utilized study emphasizes study aimed saving lives random forest leading causes influencing predictors high risk health survey encompassed 2 effectively mitigate early identification death globally blood vessels air conditioner aged 65 221 respondents 2022 data
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Important predictors of high-risk for CVD.

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