American journal of biological anthropology
39101464
OBJECTIVES: Maternal stress has long been associated with lower birthweight, which is associated with adverse health outcomes including many adult diseases. The underlying mechanisms remain elusive although changes in gene expression may play a role....
BACKGROUND: Retinopathy of prematurity (ROP), is a preventable leading cause of blindness in infants and is a condition in which the immature retina experiences abnormal blood vessel growth. The development of ROP is multifactorial; nevertheless, the...
BACKGROUND: Newborns are shaped by prenatal maternal experiences. These include a pregnant person's physical health, prior pregnancy experiences, emotion regulation, and socially determined health markers. We used a series of machine learning models ...
This study was designed to predict the post-weaning weights of Akkaraman lambs reared on different farms using multiple linear regression and machine learning algorithms. The effect of factors the age of the dam, gender, type of lambing, enterprise, ...
European journal of obstetrics, gynecology, and reproductive biology
39642647
OBJECTIVE: To develop machine learning prediction models for small for gestational age with baseline characteristics and biochemical tests of various pregnancy stages individually and collectively and compare predictive performance.
Medical science monitor : international medical journal of experimental and clinical research
39707645
BACKGROUND Subchorionic hematoma (SCH) can lead to blood accumulation and potentially affect pregnancy outcomes. Despite being a relatively common finding in early pregnancy, the effects of SCH on pregnancy outcomes such as miscarriage, stillbirth, a...
Early prediction of intraventricular hemorrhage (IVH) in very low-birthweight infants (VLBWIs) remains challenging because of multifactorial risk factors. IVH often occurs within a few hours after birth, yet its onset cannot be reliably predicted usi...
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...
BACKGROUND: To evaluate the effectiveness of machine learning (ML) models in predicting the occurrence of retinopathy of prematurity (ROP) and treatment need.
The Journal of clinical endocrinology and metabolism
39011974
CONTEXT: Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited.