AIMC Topic: Pregnant People

Clear Filters Showing 1 to 10 of 12 articles

Optimizing machine learning models for predicting health service access and determinants among pregnant women in rural Ethiopia.

Scientific reports
Pregnant women in rural Ethiopia face substantial barriers to accessing adequate healthcare services, contributing to adverse maternal and neonatal health outcomes. Traditional statistical approaches often fall short in capturing the complex, nonline...

Influencing factors for childbirth readiness among pregnant women based on the reciprocal determinism theory and backpropagation neural network: a cross-sectional study in China.

BMC pregnancy and childbirth
BACKGROUND: Childbirth readiness is essential for improving maternal health outcomes and reducing mortality, yet preparedness remains low among pregnant women globally. This study aims to identify key factors influencing childbirth readiness among Ch...

Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.

BMC public health
INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its critical importance, comprehensive data on tobacco use among pregnant women in sub-Saharan Africa i...

Utilizing machine learning to classify persistent organic pollutants in the serum of pregnant women: a predictive modeling approach.

Environmental science and pollution research international
Polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs), and per- and poly-fluoroalkyl substances (PFAS) are persistent organic pollutants (POPs) that remain de...

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.

PloS one
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...

Predicting preterm birth using explainable machine learning in a prospective cohort of nulliparous and multiparous pregnant women.

PloS one
Preterm birth (PTB) presents a complex challenge in pregnancy, often leading to significant perinatal and long-term morbidities. "While machine learning (ML) algorithms have shown promise in PTB prediction, the lack of interpretability in existing mo...

Predicting the level of anemia among Ethiopian pregnant women using homogeneous ensemble machine learning algorithm.

BMC medical informatics and decision making
BACKGROUND: More than 115,000 maternal deaths and 591,000 prenatal deaths occurred in the world per year with anemia, the reduction of red blood cells or hemoglobin in the blood. The world health organization divides anemia in pregnancy into mild ane...

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can hel...

Predicting completion of clinical trials in pregnant women: Cox proportional hazard and neural network models.

Clinical and translational science
This study aimed to develop a model for predicting the completion of clinical trials involving pregnant women using the Cox proportional hazard model and neural network model (DeepSurv) and to compare the predictive performance of both methods. We co...

Diagnosis of diabetes in pregnant woman using a Chaotic-Jaya hybridized extreme learning machine model.

Journal of integrative bioinformatics
As stated by World Health Organization (WHO) report, 246 million individuals have suffered with diabetes disease over worldwide and it is anticipated that by 2025 this estimation can cross 380 million. So, the proper and quick diagnosis of this disea...