Novel Chandra Das, Probir Kumar Ghosh, Md. Alamgir Hossain, Uddip Acharjee Shuvo et al.
INTRODUCTION: 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 screening and policy in l...
Hafeja Akhter Hima, Md Abdul Hannan Miah, Nipa Rani Ghosh, Sazia Sultana et al.
Background and Objectives: Nonalcoholic fatty liver disease (NAFLD) and polycystic ovary syndrome (PCOS) are two prevalent metabolic disorders characterized by insulin resistance. A bidirectional relationship exists between NAFLD and PCOS. NAFLD prevalence is significantly higher and more severe in ...
Novel Chandra Das, Probir Kumar Ghosh, Md. Alamgir Hossain, Uddip Acharjee Shuvo et al.
[This corrects the article DOI: 10.1371/journal.pone.0335442.].
Novel Chandra Das, Probir Kumar Ghosh, Md Alamgir Hossain, Uddip Acharjee Shuvo et al.
[This corrects the article DOI: 10.1371/journal.pone.0335442.].
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
Workflow of machine learning pipeline for hypertension prediction and risk factor ranking of married women in Bangladesh.
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
Learning curve of the ExtraTrees model for predicting hypertension among married women in Bangladesh.
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
Reliability plot of the ExtraTrees model for predicting hypertension among married women in Bangladesh.
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
b. The classification of positive and negative predictors of hypertension of married women in Bangladesh. c. The impact of the factors of married women's hypertension in Bangladesh.
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...
Novel Chandra Das (19742953), Probir Kumar Ghosh (6947282), Md. Alamgir Hossain (1371456), Uddip Acharjee Shuvo (22530303) et al.
<div> Introduction 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 screening and policy...