Predicting hypertension and identifying most important factors among married women in Bangladesh using machine learning approach.

<h4>Introduction</h4>Hypertension is a leading contributor to maternal and cardiometabolic morbidity in Bangladesh. We developed and interpreted machine-learning (ML) models to predict hypertension and rank associated factors among married women with the goal of informing targeted screen...

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出版年:	PLoS ONE
主要な著者:	Novel Chandra Das, Probir Kumar Ghosh, Md Alamgir Hossain, Uddip Acharjee Shuvo, Nipa Rani Talukder, Fatema Khatun, Mohammad Ziaul Islam Chowdhury
フォーマット:	論文
言語:	英語
出版事項:	Public Library of Science (PLoS) 2025-01-01
オンライン･アクセス:	https://doi.org/10.1371/journal.pone.0335442